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Paper Citation Record · LEDGER

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement

As of 19 August 2026, this Paper Citation Record lists 99 of 99 outbound references and 6 inbound Pith citation observations for arXiv:2508.15027.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.15027 v1

Coverage vector

measured 99 of 99 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:16:38.709392Z

measured 105 of 105 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T20:20:47.183401Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T20:37:22.595648Z

Reference resolution

99 of 99 outbound references displayed

  • verified exact0
  • verified fuzzy76
  • unresolved23
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cbb90bab-8fdb-4760-b034-45e41709f65f · outbound

This paper cites Focus- diffuser: Perceiving local disparities for camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Focus- diffuser: Perceiving local disparities for camouflaged object detection,

Reference 1

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Observation a28328b6-17b5-49bb-82f7-2cbafc13ca22 · outbound

This paper cites Conditional diffusion models for camouflaged and salient object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Conditional diffusion models for camouflaged and salient object detection,

Reference 2

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Observation 74417e2a-4cb7-4bf2-862c-149abab6daa7 · outbound

This paper cites Run: Reversible unfolding network for concealed object segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Run: Reversible unfolding network for concealed object segmentation,

Reference 3

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source=pdf_text observed=2026-08-05T18:16:29.172150Z digest=sha256:5aafb286786cfd59a65ea1f4f815a4201648bdde47c47d2027c186d2b9ae0920

Observation d01efff6-d1a7-4d01-9073-1c04512a2ba1 · outbound

This paper cites Camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Camouflaged object detection,

Reference 4

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source=pdf_text observed=2026-08-05T18:16:29.237630Z digest=sha256:8e3d8f63870527426541d57f9a8db25f9ade51147fb2e855ac24bf8be8c56e6e

Observation 67e3ad59-5ba0-4a66-9f9e-5d5df48c2ac7 · outbound

This paper cites Weakly-supervised concealed object segmentation with sam-based pseudo labeling and multi-scale feature grouping,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Weakly-supervised concealed object segmentation with sam-based pseudo labeling and multi-scale feature grouping,

Reference 5

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Observation fdb93354-993d-4852-8767-a96464e322f2 · outbound

This paper cites Strategic preys make acute predators: Enhancing camouflaged object detectors by generating camouflaged objects,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Strategic preys make acute predators: Enhancing camouflaged object detectors by generating camouflaged objects,

Reference 6

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T18:16:29.373655Z digest=sha256:797b41c7c21c0289b2aae17c952464e4172ccb0555b78f7ead162589e155d5d8

Observation 3c1dffca-8ed8-454b-993d-cecb6d01d634 · outbound

This paper cites Image threshold segmentation based on glle histogram,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Image threshold segmentation based on glle histogram,

Reference 7

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Observation af6d02db-d68f-498c-845b-f21f693645d4 · outbound

This paper cites Camouflaged object detection with feature decomposition and edge reconstruction,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Camouflaged object detection with feature decomposition and edge reconstruction,

Reference 8

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Observation b8551ea7-b32f-49af-8cc4-62a0f057c240 · outbound

This paper cites A survey of camouflaged object detection and beyond,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement A survey of camouflaged object detection and beyond,

Reference 9

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Observation 951dfeaa-52b4-4041-9e02-1ce6bac07f1e · outbound

This paper cites Concealed object segmentation with hierarchical coherence modeling,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Concealed object segmentation with hierarchical coherence modeling,

Reference 10

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Observation 710fb6d8-1d2b-4afc-a5ab-b19f9e14258f · outbound

This paper cites Pranet: Parallel reverse attention network for polyp segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Pranet: Parallel reverse attention network for polyp segmentation,

Reference 11

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Observation 71d076b1-c863-4fdc-90ee-7b975d8c4a41 · outbound

This paper cites Bilateral reference for high-resolution dichotomous image segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Bilateral reference for high-resolution dichotomous image segmentation,

Reference 12

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no resolver link, observed 2026-08-05T18:16:29.787190Z

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Observation a4c0615e-9130-4af7-acf7-c2a406fafb11 · outbound

This paper cites Segrefiner: Towards model-agnostic segmentation refinement with discrete diffusion process,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Segrefiner: Towards model-agnostic segmentation refinement with discrete diffusion process,

Reference 13

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Observation 1a8364d0-9853-47f1-b7fe-e2fe1b8b397d · outbound

This paper cites Degradation-resistant unfolding network for heterogeneous image fusion,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Degradation-resistant unfolding network for heterogeneous image fusion,

Reference 14

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Observation 29ac5fbc-1069-47b4-ba75-06e8d0eae2f6 · outbound

This paper cites Real-world image dehazing with coherence-based pseudo labeling and cooperative unfolding network,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Real-world image dehazing with coherence-based pseudo labeling and cooperative unfolding network,

Reference 15

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Observation 9fb66dda-77d8-4611-8f44-e10b265d8551 · outbound

This paper cites Optimization of lipschitz continuous functions,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Optimization of lipschitz continuous functions,

Reference 16

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Observation 4e862d84-69db-4103-b1e2-99abad5fbc7e · outbound

This paper cites Vmamba: Visual state space model,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Vmamba: Visual state space model,

Reference 17

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Unavailable: canonical work link unavailable.

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Observation 29beb3b5-a090-46c8-bb7e-57413dfa9745 · outbound

This paper cites Deep residual learning for image recognition,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Deep residual learning for image recognition,

Reference 18

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Observation c861b104-ea6d-43f5-a14e-529b8bf0fdaf · outbound

This paper cites Hqg-net: Unpaired medical image enhancement with high-quality guidance,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Hqg-net: Unpaired medical image enhancement with high-quality guidance,

Reference 19

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Observation b4976960-1e38-40ae-84fd-d1d548768812 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Deep unsupervised learning using nonequilibrium thermodynamics,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation dd7efb8e-8a7f-45e8-8fb6-1d21ebb8b48a · outbound

This paper cites Segment concealed object with incomplete supervision,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Segment concealed object with incomplete supervision,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 85c7f3ef-664a-4add-9000-a3f442763e65 · outbound

This paper cites Uncertainty-guided transformer reasoning for camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Uncertainty-guided transformer reasoning for camouflaged object detection,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 088d60bf-be40-42b4-8cc3-a1d21313d9ff · outbound

This paper cites Auto-encoding variational bayes,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Auto-encoding variational bayes,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a6521ea6-987d-4728-bfff-b8ac405916fa · outbound

This paper cites Argmax flows and multinomial diffusion: Learning categorical distributions,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Argmax flows and multinomial diffusion: Learning categorical distributions,

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8d9684ba-4634-4c08-bc81-b7d970940f7c · outbound

This paper cites Reti-diff: Illumination degradation image restoration with retinex-based latent diffusion model,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Reti-diff: Illumination degradation image restoration with retinex-based latent diffusion model,

Reference 25

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9d6018c9-fc16-47b6-8586-05c99fc37f6d · outbound

This paper cites IQPFR: An Image Quality Prior for Blind Face Restoration and Beyond.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement IQPFR: An Image Quality Prior for Blind Face Restoration and Beyond

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 948680d4-db34-44e1-9a65-f978308a40ac · outbound

This paper cites Diffir: Efficient diffusion model for image restoration,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Diffir: Efficient diffusion model for image restoration,

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8206b7f5-b142-4432-9b95-494fc5b893c2 · outbound

This paper cites Simultaneously localize, segment and rank the camouflaged objects,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Simultaneously localize, segment and rank the camouflaged objects,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:52.186362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation cab6564a-b2ae-4428-b596-498821a3333b · outbound

This paper cites Exploring figure-ground assignment mechanism in perceptual organization,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Exploring figure-ground assignment mechanism in perceptual organization,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:51.967954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3fbc7920-1e31-465e-8dba-f1a9ee9d1299 · outbound

This paper cites Frequency-spatial entanglement learning for camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Frequency-spatial entanglement learning for camouflaged object detection,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:51.834375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 37aec6dc-8ae3-45f8-8bd4-bccf7807816c · outbound

This paper cites I can find you! boundary- guided separated attention network for camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement I can find you! boundary- guided separated attention network for camouflaged object detection,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:51.697981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.214489Z digest=sha256:6846385384215e2cdb0e95801cd9c82cdd137d00f6a7ae572d2e8492bfb5d7fc

Observation 99164d47-c425-4152-854c-c8e4d1bb9818 · outbound

This paper cites Camofocus: En- hancing camouflage object detection with split-feature focal modulation and context refinement,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Camofocus: En- hancing camouflage object detection with split-feature focal modulation and context refinement,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:51.566753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.325995Z digest=sha256:54aa4096c56ba739be934f65d4f88742f382d9632df67662bdff436451274414

Observation 76ac6b03-c15e-40bb-95ce-42dce6f68f45 · outbound

This paper cites Zoom in and out: A mixed-scale triplet network for camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Zoom in and out: A mixed-scale triplet network for camouflaged object detection,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:51.360123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.350505Z digest=sha256:a770f6a74ffd942bd1e9c2706eecab1a4c5d69346d329649f0a79c37c450de52

Observation 0dd0e0f0-8b97-4d84-8c24-3c9c33b76b24 · outbound

This paper cites Zoomnext: A unified collaborative pyramid network for camou- flaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Zoomnext: A unified collaborative pyramid network for camou- flaged object detection,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:51.244354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.416364Z digest=sha256:2a3c2f30a0a61b17482ae5bb620a195947ce41ba3ec59674ce5e4ca7b853ed47

Observation 2874a214-ebad-49fc-8dfe-b1aa67bf6101 · outbound

This paper cites Segment, magnify and reiterate: Detect camouflaged objects hard way,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Segment, magnify and reiterate: Detect camouflaged objects hard way,

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-05T18:16:51.095963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.515739Z digest=sha256:c6f60a81b32e928640adeb0a275a41766f0e239445c7bfafaadb715affb32549

Observation 6cde9944-2001-44f1-aa8f-16f8f7a13407 · outbound

This paper cites Target- aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Target- aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:50.927342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.588000Z digest=sha256:e78d05d67c01fc4aa376ef3a1cee8c80b57e356a859ff1555764aa79ce303ad7

Observation aee2c253-f62c-4205-99fc-556d048fa2f7 · outbound

This paper cites Bilevel optimization with nonsmooth lower level problems,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Bilevel optimization with nonsmooth lower level problems,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:50.730117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.657638Z digest=sha256:1df61f4fea71cb5d19b4fdd466d05782b467b76c97e62ac43028c606e9e25d46

Observation fcf31dd3-6457-4b11-b762-d03dbeba11bd · outbound

This paper cites Medical image segmentation via cascaded attention decoding,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Medical image segmentation via cascaded attention decoding,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:50.566338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.713119Z digest=sha256:cd240ddda93ede777fdd2df9c2c11f55171dbd66ea60923b68335ae88b839b3d

Observation aa7ae76f-9a28-4d30-802d-7fbe5eeb7497 · outbound

This paper cites Polyp-pvt: Polyp segmentation with pyramid vision transformers,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Polyp-pvt: Polyp segmentation with pyramid vision transformers,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:50.391231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.749368Z digest=sha256:1ee1463514c307fd9703c478bbc0ef66b12d5e46a8226445b476afe806c0a483

Observation fba6173e-a189-4819-90ed-175c6d4c56cc · outbound

This paper cites Coinnet: A convolution- involution network with a novel statistical attention for automatic polyp segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Coinnet: A convolution- involution network with a novel statistical attention for automatic polyp segmentation,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:50.201188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.848351Z digest=sha256:8db74266ad8482f5b173d1bc6246f4489de04f87afe5029d3560bc5d600cef5d

Observation d08b52cb-2d5e-4abd-890d-860aebf70c1f · outbound

This paper cites Lssnet: A method for colon polyp segmentation based on local feature supplementation and shallow feature supplementation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Lssnet: A method for colon polyp segmentation based on local feature supplementation and shallow feature supplementation,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:50.067079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:31.976404Z digest=sha256:13294b3a8c130cb741badbcdb6033f92c554b2e6b2cc2f7f1c58d9c903e51bbd

Observation 1d7b6cbd-e6bc-41cc-acfd-b036d9299992 · outbound

This paper cites Cs2-net: Deep learning segmentation of curvilinear structures in medical imaging,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Cs2-net: Deep learning segmentation of curvilinear structures in medical imaging,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:49.932649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:32.124848Z digest=sha256:2ecb56d4f1f6f0ee19b943b3803259c12edfe7349d59f5ea607ba19cc8e0414e

Observation fbbbc088-2d68-4ad5-9682-c8420ab7e42b · outbound

This paper cites Dynamic snake convo- lution based on topological geometric constraints for tubular structure segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Dynamic snake convo- lution based on topological geometric constraints for tubular structure segmentation,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:49.783617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:32.305644Z digest=sha256:ad5f5edf5d9d0e18d78cbcc60221109762344e9b3460f9ed502f93659d5be40b

Observation 868d48ef-0c79-4f30-944e-d538ceed1ec3 · outbound

This paper cites Stimulus-guided adaptive transformer network for retinal blood vessel segmentation in fundus images,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Stimulus-guided adaptive transformer network for retinal blood vessel segmentation in fundus images,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:49.654041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:32.481816Z digest=sha256:1afcb97e774019cd67e3e00e9ecd0178eb1ebb7f96327e046e69a7160e721c94

Observation b5187e9f-f820-4c2b-a5fc-d95d0501b0b2 · outbound

This paper cites Topology-aware uncertainty for image segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Topology-aware uncertainty for image segmentation,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:49.472752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:32.633900Z digest=sha256:9e06669023d7ad0445169e77e81b4c793ef2cf58102be66da47dbd4729a4294d

Observation 44234c59-a72c-4071-8519-d6b81a41d4b9 · outbound

This paper cites Represent- ing topological self-similarity using fractal feature maps for accurate segmentation of tubular structures,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Represent- ing topological self-similarity using fractal feature maps for accurate segmentation of tubular structures,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:49.311996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:32.777198Z digest=sha256:5a1c9a95a6eebee3c80727e148d25fe75f65a9508fee4edc92f254b0c2a2e965

Observation 62d254a8-3fd6-4db9-b866-473ffc2474dc · outbound

This paper cites Animal camouflage analysis: Chameleon database,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Animal camouflage analysis: Chameleon database,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:49.163082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:32.853704Z digest=sha256:8e8e7c65b5d6f3513fa77196d57f14f563d4359a52cae371c042c3cc71722628

Observation 9f1f8a54-af91-477a-a5ec-c5d1fb96a650 · outbound

This paper cites Anabranch network for camouflaged object segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Anabranch network for camouflaged object segmentation,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:49.015807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:32.954692Z digest=sha256:3597136e149f5e720a8a7d2bc4653db2032a8432e753cb164961802ee81d36dd

Observation 6d852597-461c-403c-a764-61e6d7c20c0d · outbound

This paper cites Concealed object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Concealed object detection,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:48.815874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:33.035720Z digest=sha256:15e1669113305c5a4c5e4656785625bacca34117c375f5918bb06f3cbcd12285

Observation 58af48ff-f3da-48a1-96fd-a23b4a57a50d · outbound

This paper cites How to evaluate foreground maps?.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement How to evaluate foreground maps?

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:48.659019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:33.136178Z digest=sha256:6218318051d11ab393b26ad2fb8834a85ab94988d85cfdea52c85ee9dfd1e14f

Observation 4b958a96-0582-467d-93e1-dc9366561335 · outbound

This paper cites Cognitive vision inspired object segmen- tation metric and loss function,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Cognitive vision inspired object segmen- tation metric and loss function,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:48.503703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:33.224479Z digest=sha256:46dbc89dd31fe33f0179cbe3c845111ae30547ab78f4c73d448666d8654994a7

Observation 20018e53-6cd8-4efc-8e84-35f30b971ba0 · outbound

This paper cites Structure-measure: A new way to evaluate foreground maps,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Structure-measure: A new way to evaluate foreground maps,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:48.351337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:33.375331Z digest=sha256:d371b7a914726fcef0e96d63031d580d691c63251c60ec1800c5eb9602ba2270

Observation b7eb99ff-545d-41fa-8be7-3da0cba326c4 · outbound

This paper cites Res2net: A new multi-scale backbone architecture,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Res2net: A new multi-scale backbone architecture,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:48.226029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:33.498029Z digest=sha256:1d0db4f1bbb32ceb2fd4f35c5c54f8bbfe45d5113c777e3f5b4b3f871b83d52c

Observation 807c32a7-3814-4177-ba43-91c02f47991b · outbound

This paper cites Pvt v2: Improved baselines with pyramid vision transformer,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Pvt v2: Improved baselines with pyramid vision transformer,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:48.071064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:33.598325Z digest=sha256:5479bad62c8b9049bbfec24f7fdee0ff9af60ac6facf965155de7fb36aaf8783

Observation ea0744b5-7282-42ec-88cf-de9081b1e0c3 · outbound

This paper cites Don’t hit me! glass detection in real-world scenes,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Don’t hit me! glass detection in real-world scenes,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:47.877031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:33.758553Z digest=sha256:21e93246cbc0c8a3c7af6722590191692351bf28b9e93d3414c5aefe57a36563

Observation 2461c1f3-03ef-4743-b9d0-06a65bb3fdf0 · outbound

This paper cites Enhanced boundary learning for glass-like object segmen- tation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Enhanced boundary learning for glass-like object segmen- tation,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:47.680449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:33.932342Z digest=sha256:cd37352e3333798cfc0a567399ac30e7fec2fcd6cb40e5e4d659d66a8c960518

Observation 9b4cdb5c-4344-4ef6-8862-ca5a60aeaf5e · outbound

This paper cites Rfenet: towards reciprocal feature evolution for glass segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Rfenet: towards reciprocal feature evolution for glass segmentation,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:47.480884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:34.048508Z digest=sha256:a88d6c88740520a026ae995e5becda1c083779ab981cbfb6a20b425a727c2fae

Observation 33df02ef-1d74-40b5-a804-8f1e09c1f892 · outbound

This paper cites Internal-External Boundary Attention Fusion for Glass Surface Segmentation.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Internal-External Boundary Attention Fusion for Glass Surface Segmentation

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-05T18:16:34.216499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:16:34.216499Z digest=sha256:632a63c9ec4f63f73ae4b34fd355e6ae8b6bae49303d3002b54cc37a3ee87919

Observation 27d5d378-d35b-44d6-a982-6ef74bac62d5 · outbound

This paper cites Ghostingnet: A novel approach for glass surface detection with ghosting cues,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Ghostingnet: A novel approach for glass surface detection with ghosting cues,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:47.295241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:34.362647Z digest=sha256:2ed744dc17d3b7189419e486486fb05e3d7397313e728fd389f488903538ee21

Observation 8fe7fe9e-4a59-4124-95a2-0ac11db7c1cd · outbound

This paper cites Automated polyp detection in colonoscopy videos using shape and context information,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Automated polyp detection in colonoscopy videos using shape and context information,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:47.104916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:34.511261Z digest=sha256:f2d31853b0f71b182912bcdddd06d00f13060eccf5071b67d73b6487b6b27135

Observation a1d74459-b7e3-4f42-9bed-d39617239f9c · outbound

This paper cites Toward embedded detection of polyps in wce images for early diagnosis,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Toward embedded detection of polyps in wce images for early diagnosis,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:46.901163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:34.686508Z digest=sha256:af44c9175c2abb28d09a61af5b4ac4cfa2af4524380fa8be49c254ed523c9694

Observation 98de579f-c16e-49eb-a95b-cf16bf53920d · outbound

This paper cites Struc- ture and illumination constrained gan for medical image enhancement,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Struc- ture and illumination constrained gan for medical image enhancement,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:46.727870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:34.808167Z digest=sha256:36644b8b5d283bb69eb977c614b57dbb712b7fbe8b008c3925fb15cac82caec8

Observation 5e1c064c-855b-4bf9-a61d-50b6e7421464 · outbound

This paper cites High-resolution iterative feedback network for camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement High-resolution iterative feedback network for camouflaged object detection,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:46.543174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:34.922976Z digest=sha256:6f5e8186ceaa268ff1009e2e3b57dbb3385b2ef15d8fe4eba1a9ba4b0678baee

Observation 148b95a3-e844-4582-bba2-3b35119da8ea · outbound

This paper cites Camoformer: Masked separable attention for camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Camoformer: Masked separable attention for camouflaged object detection,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:46.367958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:34.993684Z digest=sha256:bda5592947acaf6967af019fbab36898a385b7456a39d91d3e8d430e3fcc562f

Observation 39263e13-adf8-49ae-a44f-d458b55c0fe9 · outbound

This paper cites Oaformer: Occlusion aware transformer for camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Oaformer: Occlusion aware transformer for camouflaged object detection,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:46.174735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:35.085297Z digest=sha256:d83893fa4066e8ad8cebd74b820a596cffee534356d23afe5da6751f3587f375

Observation c85abb48-162a-40f1-a91b-c5fb1bfd3add · outbound

This paper cites Sam-adapter: Adapting segment anything in underperformed scenes,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Sam-adapter: Adapting segment anything in underperformed scenes,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:45.958397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:35.170540Z digest=sha256:04fa49e8c0b789f9e290c4ead1ae280ed9c1271f671c1f8f2f37cd40be9339ac

Observation 7c31d888-f1bb-4efe-9fc0-5c5e9f131951 · outbound

This paper cites Weakly-supervised camouflaged object detection with scribble,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Weakly-supervised camouflaged object detection with scribble,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:45.721085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:35.259986Z digest=sha256:ae8c67fc70398d68ce9cdcf1980a3566369ab3994c8d5a1fdbddb23a5a5e5d8e

Observation f1b291ff-084a-4d45-841d-63f2d6e50e27 · outbound

This paper cites Relax image-specific prompt requirement in sam: A single generic prompt for segmenting camouflaged objects,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Relax image-specific prompt requirement in sam: A single generic prompt for segmenting camouflaged objects,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:45.474646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:35.366331Z digest=sha256:3b8d1716e7780c5a93491a2275e5f7c30cdf53c71cb90bc7ce329cd499c3c448

Observation 2d2cbb5d-0c05-4f17-b6b1-eba7a9af99b1 · outbound

This paper cites Pseudo-label guided contrastive learning for semi- supervised medical image segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Pseudo-label guided contrastive learning for semi- supervised medical image segmentation,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:45.213695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:35.481425Z digest=sha256:86c824ca5aec83a0878ce60b3b1d762b0d56b4eff84aa893385f0ccd32f50e3c

Observation f3d324cf-35ca-48e2-8925-22ef46bd574e · outbound

This paper cites Saliency as pseudo-pixel supervision for weakly and semi-supervised semantic segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Saliency as pseudo-pixel supervision for weakly and semi-supervised semantic segmentation,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:44.936043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:35.615841Z digest=sha256:42fefeed8379f1fe6b61298cfa9c9731636e623c541ef91fc745c9c146d4e7dc

Observation 6f51dd34-5c49-4e27-8756-f3a0563b8bee · outbound

This paper cites Unsupervised and semi-supervised co-salient object detection via segmentation fre- quency statistics,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Unsupervised and semi-supervised co-salient object detection via segmentation fre- quency statistics,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:44.717404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:35.693745Z digest=sha256:53bbe21184cb8fa47bd55cfbc4d2f2706ee350cbdad584a8e111deb14b857dac

Observation c9c3cede-3810-4259-80db-2b023475433e · outbound

This paper cites Source-free depth for object pop-out,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Source-free depth for object pop-out,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:44.499096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:35.844453Z digest=sha256:a6b93b93456ecff5571851df37c28c914b2e0d6fb3106a3bc1a02842c6ff2dbd

Observation 03cd4c78-fa6e-4682-aa51-ba7cc04bccb5 · outbound

This paper cites Integrating Extra Modality Helps Segmentor Find Camouflaged Objects Well.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Integrating Extra Modality Helps Segmentor Find Camouflaged Objects Well

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-05T18:16:35.967069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:16:35.967069Z digest=sha256:27048dff8ccd0f9c496795d13e912bcf5195f4075eeb03ee642cc168ab156a4e

Observation 88bad39a-612c-4425-afe9-058aa7c7204c · outbound

This paper cites Specificity- preserving rgb-d saliency detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Specificity- preserving rgb-d saliency detection,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:44.260164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:36.038426Z digest=sha256:d34a4781fca59f70fbf4c37910ad6180c8ca65020b8a074e6aef2d08692e66fa

Observation 90abc8b5-e9ca-4296-8498-530946148652 · outbound

This paper cites Spsn: Superpixel prototype sam- pling network for rgb-d salient object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Spsn: Superpixel prototype sam- pling network for rgb-d salient object detection,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:43.954849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:36.161819Z digest=sha256:09e02575a0d7205e19fbb0a34dd05c72131966406b5142916998f6c58413527c

Observation 52a1fadb-dd43-4df0-a068-39cd695ba443 · outbound

This paper cites Exploring deeper! segment anything model with depth perception for camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Exploring deeper! segment anything model with depth perception for camouflaged object detection,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:43.660506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:36.256306Z digest=sha256:087294033cec5c80eb3248cebb8f66316a57e1b92dcc0d71273c149de9de9dde

Observation f003c0e8-852d-44d8-b8fa-a5c693f59375 · outbound

This paper cites Advances in deep concealed scene understanding,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Advances in deep concealed scene understanding,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:43.326742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:36.363526Z digest=sha256:3c0d9c513f4291bb3ed11a88bf898589a933b218877c9db1ec9f39a8727c86e6

Observation 9d24d3fc-c803-41de-b1ae-9a499772af81 · outbound

This paper cites Progressively normalized self-attention network for video polyp seg- mentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Progressively normalized self-attention network for video polyp seg- mentation,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:43.160137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:36.446161Z digest=sha256:5971fd8af9b319a62eceefddee79b1ff0fac5eeb5dbb1e4df7f8d766aa114f19

Observation e3732460-266d-4752-8c3d-68e3c9847f94 · outbound

This paper cites Self- supervised video object segmentation by motion grouping,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Self- supervised video object segmentation by motion grouping,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:43.027843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:36.591106Z digest=sha256:c7a974d18a99197742d4ea5e39f7d3c526d36dcc65cbb0865d0c8d12222b1c7b

Observation 9b30a764-66ab-4230-b268-67a87d1e1940 · outbound

This paper cites Implicit motion handling for video camouflaged object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Implicit motion handling for video camouflaged object detection,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:42.849511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:36.686317Z digest=sha256:22fc1bb05ab514613f10cf632e69517184f0bfadf99e6a05d7b5008051bdc020

Observation cc154638-9d89-4204-b4d2-7e7964307d65 · outbound

This paper cites It’s moving! a probabilistic model for causal motion segmentation in moving camera videos,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement It’s moving! a probabilistic model for causal motion segmentation in moving camera videos,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:42.677751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:36.805497Z digest=sha256:f523ea403cd713375307abb27176e154f09d8f74029eb8d9ad63765216d54a1a

Observation d466a049-43e6-471a-a8e9-e0f8a93e4885 · outbound

This paper cites Efficient inference in fully connected crfs with gaussian edge potentials,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Efficient inference in fully connected crfs with gaussian edge potentials,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:42.479877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:36.901311Z digest=sha256:472f73aca4de2ed63ddd7f42aee85686ec55ad79347f22795fb7d64c8e55279b

Observation 224af593-9de1-4243-ab79-95670bad1faf · outbound

This paper cites The fast bilateral solver,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement The fast bilateral solver,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:42.138066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:37.010596Z digest=sha256:8649f32c0e3730ce11820a219e26e7d5925fbc63ebdd7ff3f583ffcb10274d4c

Observation df6ee7fc-2287-4f8c-8b3a-c89a11e5820a · outbound

This paper cites Samrefiner: Taming segment anything model for universal mask refinement,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Samrefiner: Taming segment anything model for universal mask refinement,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:41.839348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:37.106124Z digest=sha256:d58cd2d01b3d17b9ab63a7e654d3befdee552ed56bca75ad5243dd7206ac5c78

Observation c11d6856-6b4f-44bf-b2a6-1f0146279d5d · outbound

This paper cites Visual saliency transformer,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Visual saliency transformer,

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:41.634903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:37.226081Z digest=sha256:78cabc3e6adb099fd85e3f212bb3e82b5808fe22891ab6f9e0a053e9087ed734

Observation 0bc0a2de-a32f-4cca-b8f4-4c08d4827f5a · outbound

This paper cites Salient object detection via integrity learning,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Salient object detection via integrity learning,

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:41.454027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:37.316083Z digest=sha256:ac7fe87b78a67bd7fcc60b6c4d1372a4e0a7e572d3702307348eb0c711ff1f5d

Observation f605393b-bf74-43c2-a30f-d1d64548b770 · outbound

This paper cites Pyramid grafting network for one-stage high resolution saliency detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Pyramid grafting network for one-stage high resolution saliency detection,

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:41.254335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:37.384778Z digest=sha256:34ecd02dac1557fca934fd1131af074a9bf0dd9b4b808c5dd32b2c85250fbb24

Observation 68609bc0-0763-486f-a5a8-e15b7dab43ec · outbound

This paper cites Pixels, regions, and objects: Multiple enhancement for salient object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Pixels, regions, and objects: Multiple enhancement for salient object detection,

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:41.002689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:37.525487Z digest=sha256:803199e8fd414d3cc514224199b8a884bba86a2fc108d4861257c90628b819a5

Observation a5e5b3e4-7189-4937-8297-dfd3e69f00f5 · outbound

This paper cites Recurrent multi-scale transformer for salient object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Recurrent multi-scale transformer for salient object detection,

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:40.748615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:37.676930Z digest=sha256:a93c28478e44cbc125973629c81ed97732cb8f82429d69f894c8207960dd0bec

Observation 16e3e006-d7f9-4159-b776-b0865c9a6457 · outbound

This paper cites Gponet: A two-stream gated progressive optimization network for salient object detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Gponet: A two-stream gated progressive optimization network for salient object detection,

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:40.474947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:37.759540Z digest=sha256:17f0f9b49fc79191db6e0555b1153b615d0f380f914b12c4114838af2db3f291

Observation 4d27e907-5d1f-4d45-8e7e-cf89866ac368 · outbound

This paper cites Efficient and stronger visual saliency transformer,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Efficient and stronger visual saliency transformer,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:40.267465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:37.864920Z digest=sha256:ebe0faf0d07f348a6798139ec829f7f934f11ad8267f61d3c8432c3af048e51a

Observation f84d4bd0-2592-49ce-9b63-184056a30dc6 · outbound

This paper cites UnfoldIR: Rethinking Deep Unfolding Network in Illumination Degradation Image Restoration.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement UnfoldIR: Rethinking Deep Unfolding Network in Illumination Degradation Image Restoration

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-05T18:16:37.994325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:16:37.994325Z digest=sha256:181dd6fde79a841e5dc32f8ad09e4d7446a07963eda0cd85c8832d4bcde9cca6

Observation 380d5b8c-7b65-40eb-849e-ba7d7d899402 · outbound

This paper cites Getting to know low-light images with the exclusively dark dataset,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Getting to know low-light images with the exclusively dark dataset,

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:40.024448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:38.075382Z digest=sha256:d01d2b1f4270bc9ce8c2c05075acf1c347ee5fb03a1ef1e48a5599575af923ba

Observation 5936944c-acca-424f-9383-e8db9e460d7d · outbound

This paper cites Diff-retinex: Rethinking low-light image enhancement with a generative diffusion model,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Diff-retinex: Rethinking low-light image enhancement with a generative diffusion model,

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:39.786545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:38.218894Z digest=sha256:5195be22cbf03cf0dd27f24b6c322f0196e83f6fe10581ef34417eddb5b5375f

Observation 811f2e93-8818-4dd1-948b-c513b9a8197f · outbound

This paper cites Saliency detection via graph-based manifold ranking,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Saliency detection via graph-based manifold ranking,

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:39.643804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:38.326132Z digest=sha256:fef4f820ef67e78c3e0aedff247ab18935b5962d8fd379a759909f8108bc6ff0

Observation 8ab43231-72f9-4ba0-9df8-455547dfe5bf · outbound

This paper cites Learning to detect salient objects with image-level supervision,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Learning to detect salient objects with image-level supervision,

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:39.470761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:38.428066Z digest=sha256:69f1fcf8439a19af538e20850200b797bcc7f8baa645483b285c1b0d17569481

Observation a009b336-823a-4039-82da-c2891162176a · outbound

This paper cites Hierarchical saliency detection,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Hierarchical saliency detection,

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:39.318951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:38.520162Z digest=sha256:7238a68dbc53547b4b38bb89c19bb0f3a92bfb138ebf482258b959c7d9a61b8e

Observation 7fc150ea-3b2a-4c04-a370-ccc937114ef4 · outbound

This paper cites Visual saliency based on multiscale deep features,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement Visual saliency based on multiscale deep features,

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:39.123479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:38.635633Z digest=sha256:84d577518daa425639aa60aceffc9e54d91965eb409d38d8316118a979882c25

Observation 709c93a2-3a93-4ca9-866f-812a6600c420 · outbound

This paper cites The secrets of salient object segmentation,.

Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement The secrets of salient object segmentation,

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T18:16:38.930203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T18:16:38.709392Z digest=sha256:8e11590bcd91ab6156c07e4b184a35799d413e5047ec2cacc3322474dfac4506

Pith citing papers

Observation e6003869-cc04-4033-a13c-01e594a174cb · inbound

Beyond Ground-Truth: Leveraging Image Quality Priors for Real-World Image Restoration cites this paper.

Beyond Ground-Truth: Leveraging Image Quality Priors for Real-World Image Restoration Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-14T00:08:28.720394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-14T00:07:16.009279Z digest=sha256:4752077a93fccc442c979bb3e31fa51fd2563ebe44388ac93a40b4843d660730

Observation 14000647-618a-4ef5-804b-02b8c3833006 · inbound

GS-STVSR: Ultra-Efficient Continuous Spatio-Temporal Video Super-Resolution via 2D Gaussian Splatting cites this paper.

GS-STVSR: Ultra-Efficient Continuous Spatio-Temporal Video Super-Resolution via 2D Gaussian Splatting Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:40:19.548925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T04:46:39.643664Z digest=sha256:24edae34515bc6878585dd2d5a4cd1043df9716566b507f85201e1cf0ac34dd2

Observation 07363b8d-4396-4d37-9199-dfae272b1ae6 · inbound

Learning to Track Instance from Single Nature Language Description cites this paper.

Learning to Track Instance from Single Nature Language Description Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:45:51.056369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-11T01:44:31.308036Z digest=sha256:761b84b62cce469adb7c45a0b1b1da22cb727f510cbcb646e448eb11213d5f53

Observation 31860bf0-af10-4d2a-81cd-28ce58827779 · inbound

RIDE: Retinex-Informed Decoupling for Exposing Concealed Objects cites this paper.

RIDE: Retinex-Informed Decoupling for Exposing Concealed Objects Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-19T15:12:37.444018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-19T15:11:55.921453Z digest=sha256:29cdd623a138d7118e3ee7dab95cdf7885462b330933a3053171cc9e777d6068

Observation a0e43fea-3b90-4412-be94-0ac77a26a75d · inbound

Embedding-perturbed Exploration Preference Optimization for Flow Models cites this paper.

Embedding-perturbed Exploration Preference Optimization for Flow Models Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-20T18:38:53.024747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-20T18:33:52.933672Z digest=sha256:f821e8ee214bbe678c401257b1e28d631e440d920e75461eb7c7d9246cf383b2

Observation eb2a8ae0-8987-493a-bd84-6fb2bdd136a4 · inbound

On the Controllability-Fidelity Frontier in Diffusion Editing cites this paper.

On the Controllability-Fidelity Frontier in Diffusion Editing Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-02T20:37:22.597175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-27T20:20:47.183401Z digest=sha256:6ef38b79b52276ab320a9e2f80973436b53b8eb215541012fa4690598847ec09