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Paper Citation Record · LEDGER

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation

As of 16 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2412.02322.

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

pith.paper-citation-record.v1
2412.02322 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:41:15.565723Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:44:40.378637Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T14:44:40.583939Z

Reference resolution

53 of 53 outbound references displayed

  • verified exact0
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  • unresolved28
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation be275b4c-40d4-4128-8f1a-f92261413680 · outbound

This paper cites Shadowformer: Global context helps shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Shadowformer: Global context helps shadow removal,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 06ebf6fd-02ac-4e93-b50f-63abec3ece24 · outbound

This paper cites Leveraging inpainting for single-image shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Leveraging inpainting for single-image shadow removal,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 9c11d65d-ce22-4c22-9b17-28d7a7ccf107 · outbound

This paper cites A shadow imaging bilinear model and three-branch residual network for shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation A shadow imaging bilinear model and three-branch residual network for shadow removal,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 9d86a6c7-3d2d-4c2e-9cba-3045bdb46688 · outbound

This paper cites Homoformer: Homogenized transformer for image shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Homoformer: Homogenized transformer for image shadow removal,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5d3224f1-fadc-4f8d-aa72-51dc7d4f2c3d · outbound

This paper cites Shadow removal via shadow image decompo- sition,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Shadow removal via shadow image decompo- sition,

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1ce5282d-ef96-4afb-b0e0-f63346f78473 · outbound

This paper cites Denoising diffusion probabilistic models,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Denoising diffusion probabilistic models,

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6fbbc2f5-202f-481e-ba61-531fd9267792 · outbound

This paper cites Denoising Diffusion Implicit Models.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Denoising Diffusion Implicit Models

Reference 7

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Unavailable: canonical work link unavailable.

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Observation c88b5949-9e8c-4758-9072-c63349b07e10 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation High- resolution image synthesis with latent diffusion models,

Reference 8

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Observation abef9ffa-cd3a-4cea-95ba-f4f9de84b2f5 · outbound

This paper cites Adding conditional control to text-to-image diffusion models,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Adding conditional control to text-to-image diffusion models,

Reference 9

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Unavailable: canonical work link unavailable.

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Observation 8fd7610e-2af9-468b-b7d0-717fed2649a7 · outbound

This paper cites Sgdm: An adaptive style- guided diffusion model for personalized text to image generation,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Sgdm: An adaptive style- guided diffusion model for personalized text to image generation,

Reference 10

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Unavailable: canonical work link unavailable.

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Observation b7a605eb-c329-4b3f-aad0-b521660fd675 · outbound

This paper cites Animediff: Customized image generation of anime characters using diffusion model,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Animediff: Customized image generation of anime characters using diffusion model,

Reference 11

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Source-reported events for the cited work

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Observation d3a4d6cc-97ef-45ea-af3f-428673924b4a · outbound

This paper cites DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior

Reference 12

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Unavailable: canonical work link unavailable.

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Observation af14117f-dfd4-4ec2-a183-23e0181888b8 · outbound

This paper cites Diffusion Model for Generative Image Denoising.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Diffusion Model for Generative Image Denoising

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 770b240e-b590-4f62-b7aa-59d768418c42 · outbound

This paper cites Denoising diffusion restoration models,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Denoising diffusion restoration models,

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bdc8f040-9034-4230-9d69-225183785bb0 · outbound

This paper cites Controlling Vision-Language Models for Multi-Task Image Restoration.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Controlling Vision-Language Models for Multi-Task Image Restoration

Reference 15

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Observation af6b62c5-23f2-4146-a788-a839aa24a9cc · outbound

This paper cites Residual de- noising diffusion models,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Residual de- noising diffusion models,

Reference 16

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Observation 0724c5fc-f09e-4859-ac5f-f45adb1efb00 · outbound

This paper cites The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale,

Reference 17

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Observation adb270a1-bdc5-44c0-a61c-23606ab80b54 · outbound

This paper cites Laion- 5b: An open large-scale dataset for training next generation image-text models,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Laion- 5b: An open large-scale dataset for training next generation image-text models,

Reference 18

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Unavailable: canonical work link unavailable.

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Observation 8b8aee64-8d98-4fb6-82ad-ef523473bb48 · outbound

This paper cites Shadow remover: Image shadow removal based on illumination recovering optimization,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Shadow remover: Image shadow removal based on illumination recovering optimization,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation ed39db93-3d41-4430-9ff0-bd211e588659 · outbound

This paper cites The shadow meets the mask: Pyramid-based shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation The shadow meets the mask: Pyramid-based shadow removal,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation bf4ff419-d77f-4eda-97fc-0e537b838d64 · outbound

This paper cites On the removal of shadows from images,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation On the removal of shadows from images,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation f622ed7d-19da-4d5d-8977-b3def52330c8 · outbound

This paper cites Learning to remove soft shadows,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Learning to remove soft shadows,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation d2b2af3e-8bf4-4d61-b667-cff3f80d92c6 · outbound

This paper cites Paired regions for shadow detection and removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Paired regions for shadow detection and removal,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 404335cf-7688-40a8-a285-f6b740601ae9 · outbound

This paper cites Leave-one-out kernel optimization for shadow detection and removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Leave-one-out kernel optimization for shadow detection and removal,

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 2a05c70f-7f41-4a24-947f-e0f02df601d3 · outbound

This paper cites Stacked conditional generative adversarial networks for jointly learning shadow detection and shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Stacked conditional generative adversarial networks for jointly learning shadow detection and shadow removal,

Reference 25

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Observation bdb6414e-1c0a-472d-bd19-74bf57d8d802 · outbound

This paper cites Auto-exposure fusion for single-image shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Auto-exposure fusion for single-image shadow removal,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation c1bf4efd-0786-494c-82f4-c26940af488d · outbound

This paper cites A boundary-aware network for shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation A boundary-aware network for shadow removal,

Reference 27

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raw_fallback, observed 2026-08-11T23:41:15.921318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 8db3fe87-39e4-41b4-857f-6c79c100ee1b · outbound

This paper cites Des3: Adaptive attention-driven self and soft shadow removal using vit similarity,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Des3: Adaptive attention-driven self and soft shadow removal using vit similarity,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation eac5f6cb-3c88-4be2-84bb-b185cb95bddc · outbound

This paper cites Mask-shadowgan: Learn- ing to remove shadows from unpaired data,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Mask-shadowgan: Learn- ing to remove shadows from unpaired data,

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:41:15.468798Z digest=sha256:855611315e734401942a258bd2026c382568354217688d23d547af72ba91ebde

Observation 3c3ee387-a58d-438c-8667-ac59a0a2b4e2 · outbound

This paper cites Towards ghost-free shadow removal via dual hierarchical aggregation network and shadow matting gan,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Towards ghost-free shadow removal via dual hierarchical aggregation network and shadow matting gan,

Reference 30

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raw_fallback, observed 2026-08-11T23:41:15.892768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 2f870fb7-2d7e-4d61-9d67-19d31c4cd7d3 · outbound

This paper cites Dc-shadownet: Single-image hard and soft shadow removal using unsupervised domain-classifier guided network,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Dc-shadownet: Single-image hard and soft shadow removal using unsupervised domain-classifier guided network,

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a744e557-59b1-4c0b-89c1-c195f055780f · outbound

This paper cites A decoupled multi- task network for shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation A decoupled multi- task network for shadow removal,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 671e8d61-f255-447a-a6ee-006232c9fe4a · outbound

This paper cites Mmginpainting: Multi-modality guided image inpainting based on diffusion models,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Mmginpainting: Multi-modality guided image inpainting based on diffusion models,

Reference 33

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raw_fallback, observed 2026-08-11T23:41:15.867658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5859f223-9909-4411-8e05-6c2ee69d1968 · outbound

This paper cites Wavedm: Wavelet-based diffusion models for image restoration,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Wavedm: Wavelet-based diffusion models for image restoration,

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation fed135e5-e5a6-422c-be27-e80024814daf · outbound

This paper cites Shadowdiffusion: When degradation prior meets diffusion model for shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Shadowdiffusion: When degradation prior meets diffusion model for shadow removal,

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:41:15.495510Z digest=sha256:c14e559c42e83f5431cd5d734661f53f0978f2421a3caf970992b7f3a3f027f0

Observation 1b0cd54f-662e-429d-b350-5ddf0156b714 · outbound

This paper cites Latent feature-guided diffusion models for shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Latent feature-guided diffusion models for shadow removal,

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-11T23:41:15.841610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:41:15.499426Z digest=sha256:d26734eb67fb1f47f8a0ac26a590a76ab4cfc10ff7600f1ed3e7d8c2756a57d1

Observation 309a67e8-0e84-4194-80e3-bd9ddfadfc18 · outbound

This paper cites Scaling up to excellence: Practicing model scaling for photo- realistic image restoration in the wild,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Scaling up to excellence: Practicing model scaling for photo- realistic image restoration in the wild,

Reference 37

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source=pdf_text observed=2026-08-11T23:41:15.503781Z digest=sha256:88b63f4e93d63806aa083f6456ea156641a34c108e736564a304a469dc89d123

Observation 9b9f89e5-1bf7-4b66-8a2b-9a5e445ff64d · outbound

This paper cites Seesr: Towards semantics-aware real-world image super-resolution,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Seesr: Towards semantics-aware real-world image super-resolution,

Reference 38

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source=pdf_text observed=2026-08-11T23:41:15.507420Z digest=sha256:aaadcc0ff1c98f0e057d1659ec1b78d3068acd67f2d89286fa5043e066df99c4

Observation da86de8e-0ef2-47b7-892b-1a734eecbefe · outbound

This paper cites Paint by example: Exemplar-based image editing with diffusion models,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Paint by example: Exemplar-based image editing with diffusion models,

Reference 39

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no resolver link, observed 2026-08-11T23:41:15.511011Z

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source=pdf_text observed=2026-08-11T23:41:15.511011Z digest=sha256:100721b2cbea57ebbb0a670025d7951812fc72a5a67535513db576e500fdcd61

Observation 4733ea0b-1626-41cc-ae89-ba7d200c9dd7 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Momentum contrast for unsupervised visual representation learning,

Reference 40

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no resolver link, observed 2026-08-11T23:41:15.514593Z

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source=pdf_text observed=2026-08-11T23:41:15.514593Z digest=sha256:278101250f2faec65f7324f96103f0aefaab98b56f70674b81bbfa87d43b85ca

Observation 9a7d9e07-0bac-4c92-a954-ab2c2a3e1c34 · outbound

This paper cites Taming transformers for high- resolution image synthesis,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Taming transformers for high- resolution image synthesis,

Reference 41

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source=pdf_text observed=2026-08-11T23:41:15.518500Z digest=sha256:117ddcb175a551b62443f163b8485790511bc5fe95700e90f103a5b7b5bf96e0

Observation 551266e5-429d-4af6-8960-40f6583aa13a · outbound

This paper cites Designing a Better Asymmetric VQGAN for StableDiffusion.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Designing a Better Asymmetric VQGAN for StableDiffusion

Reference 42

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no resolver link, observed 2026-08-11T23:41:15.522974Z

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source=pdf_text observed=2026-08-11T23:41:15.522974Z digest=sha256:08d42234bb9aa00e76c05ad2513a9ba60d03ac8161b97784ec80b763ff3aa5ce

Observation b8a2b46f-92a3-456e-a4a1-eece0d0a01e4 · outbound

This paper cites Deformable convnets v2: More deformable, better results,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Deformable convnets v2: More deformable, better results,

Reference 43

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source=pdf_text observed=2026-08-11T23:41:15.527783Z digest=sha256:1e57574245a57c251f802fc1309546af0bac803e09037d315624be8c00a101a4

Observation cb392ef8-a113-442c-b63d-927dce4148b1 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Learning transferable visual models from natural language supervision,

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-11T23:41:15.794876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:41:15.531708Z digest=sha256:10c2eb153f37afe299c642e35e0a215bed898ab811c0e1209311b69e9e83e49d

Observation bc4acb92-2b6e-4098-ab64-e8fff4567543 · outbound

This paper cites Physics-based shadow image decomposition for shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Physics-based shadow image decomposition for shadow removal,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:41:15.784749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:41:15.535723Z digest=sha256:0856c0900e38acb382ff3852c8cd6c25c0d5aed1063c9ce750813353087bf4cd

Observation 5fe8f93e-7974-464b-b48f-c62c8219a4ac · outbound

This paper cites Deshadownet: A multi- context embedding deep network for shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Deshadownet: A multi- context embedding deep network for shadow removal,

Reference 46

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verified fuzzy
raw_fallback, observed 2026-08-11T23:41:15.774612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:41:15.538927Z digest=sha256:a6b9960e52b1d5c0ad05555ca213e4d7ac996732a1dbc4cd7723f23a9ed22d10

Observation 5eb434b7-3bf2-41c3-bd4a-f453bc93a6d4 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation The unreasonable effectiveness of deep features as a perceptual metric,

Reference 47

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source=pdf_text observed=2026-08-11T23:41:15.542523Z digest=sha256:b5d56a939864914be1c0e23101172b1e75390d28b85c1e427ae03f268eabfc56

Observation 7a101f1f-a202-4ba3-bf2d-876df120be8f · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Gans trained by a two time-scale update rule converge to a local nash equilibrium,

Reference 48

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unresolved
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source=pdf_text observed=2026-08-11T23:41:15.545775Z digest=sha256:add47eb2da2329b14c2eed1aef088e6198672879e89a6f303a2cc824f1008dfa

Observation 569e8a31-ebef-4154-afb7-b22fb2dfbc04 · outbound

This paper cites Direction-aware spatial context features for shadow detection,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Direction-aware spatial context features for shadow detection,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:41:15.752585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:41:15.550369Z digest=sha256:a4f672d6620dbe8337416df22578f6d89160c36242b7030b13fc19a8fb1a9f8d

Observation b5a3eaed-48b9-47fc-aa6d-760f63eb2301 · outbound

This paper cites Shadow removal by a lightness-guided network with training on unpaired data,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Shadow removal by a lightness-guided network with training on unpaired data,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:41:15.742403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:41:15.555056Z digest=sha256:b22cd1d5d313b52de7d414bb6b96da035095184ad66fc29f79950704fcac4255

Observation 901a9cca-a4ca-4a41-abac-6a13b89cc230 · outbound

This paper cites Unveiling deep shadows: A survey on image and video shadow detection, removal, and generation in the era of deep learning,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Unveiling deep shadows: A survey on image and video shadow detection, removal, and generation in the era of deep learning,

Reference 51

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source=pdf_text observed=2026-08-11T23:41:15.558639Z digest=sha256:40687dbbc0c3e26865d81369ebd6d721b2a40cc2e18f2edbb81491d6f7897a5b

Observation 82880992-053b-4a07-9423-77f3bf5cbe52 · outbound

This paper cites Style- guided shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Style- guided shadow removal,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:41:15.730949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:41:15.562005Z digest=sha256:bb95e5c5d28e61310893434029a7c70647df8a669c32a664a433a9a9cda8a041

Observation dcf493f4-2c25-434f-a80f-bcaa27da5f29 · outbound

This paper cites Bijective mapping network for shadow removal,.

Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation Bijective mapping network for shadow removal,

Reference 53

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source=pdf_text observed=2026-08-11T23:41:15.565723Z digest=sha256:6dec0686ab0da185947aece43c755caa658265888ae13a6c27485c2d48126dc9

Pith citing papers

Observation 6872aa30-d46e-4e1c-888e-e5a9cf4dbff6 · inbound

Prompt-Aware Controllable Shadow Removal cites this paper.

Prompt-Aware Controllable Shadow Removal Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation

Reference 16

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verified exact
local_arxiv, observed 2026-08-10T14:44:40.589080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-10T14:44:40.378637Z digest=sha256:a01f4af34da2cb2ffe786db5fe8b3999675b8809a225c59c1e890b0c54a7b9ff