Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-10T13:54:17.552706Z
Paper Citation Record · LEDGER
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization
As of 15 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2604.13383.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
57 of 57 outbound references displayed
- verified exact4
- verified fuzzy50
- unresolved3
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b86fd20e-9cc8-42eb-9bc1-20f0a39d6a5d · outbound
This paper cites Argan: Attentive recurrent generative adversarial network for shadow detection and removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Argan: Attentive recurrent generative adversarial network for shadow detection and removal
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.035625Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b9fab638-dcc5-4123-ac35-11387bccd678 · outbound
This paper cites Shadowrefiner: Towards mask-free shadow removal via fast fourier transformer.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Shadowrefiner: Towards mask-free shadow removal via fast fourier transformer
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.039238Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6a776e89-f088-4f7c-b7ae-be68345b22ac · outbound
This paper cites Dehazedct: Towards effective non- homogeneous dehazing via deformable convolutional trans- former.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Dehazedct: Towards effective non- homogeneous dehazing via deformable convolutional trans- former
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.031947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 421c803b-2edc-4a33-b0ff-98540f03909a · outbound
This paper cites Ecmamba: Consolidating selective state space model with retinex guidance for efficient multiple exposure correc- tion.Advances in Neural Information Processing Systems.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Ecmamba: Consolidating selective state space model with retinex guidance for efficient multiple exposure correc- tion.Advances in Neural Information Processing Systems
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.202885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5f22a597-3797-406e-8174-8f3394e36c4c · outbound
This paper cites To- wards scale-aware low-light enhancement via structure- guided transformer design.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization To- wards scale-aware low-light enhancement via structure- guided transformer design
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.145709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 046600f5-6237-43fc-8e21-ce1dc838af4b · outbound
This paper cites Retinex-guided histogram transformer for mask-free shadow removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Retinex-guided histogram transformer for mask-free shadow removal
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.212990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b24cab0e-0e51-4f7c-9a70-378562dd8537 · outbound
This paper cites Zero- reference joint low-light enhancement and deblurring via vi- sual autoregressive modeling with vlm-derived modulation.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Zero- reference joint low-light enhancement and deblurring via vi- sual autoregressive modeling with vlm-derived modulation
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.150297Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6ae3e6fc-fc51-4c1f-badf-3a15a73a1d0a · outbound
This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization An image is worth 16x16 words: Trans- formers for image recognition at scale
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.057564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c5ff7282-a61d-49a8-a354-ed744d32298d · outbound
This paper cites Finlayson, Steven D.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Finlayson, Steven D
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.206239Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 72a7ae55-7217-4a8a-9709-61ae1eb9c9bd · outbound
This paper cites Finlayson, Steven D.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Finlayson, Steven D
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.188905Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2799a82c-0ec7-4df4-823c-501c1baec967 · outbound
This paper cites Finlayson, Mark S.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Finlayson, Mark S
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.192048Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0289d1cf-cabf-4cf5-b36c-1465a4416b52 · outbound
This paper cites Shadowformer: Global context helps image shadow re- moval.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Shadowformer: Global context helps image shadow re- moval
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.209727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5df6b03d-cbc5-4c4d-ab59-fdf47764c82e · outbound
This paper cites Shadowd- iffusion: When degradation prior meets diffusion model for shadow removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Shadowd- iffusion: When degradation prior meets diffusion model for shadow removal
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.124824Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c72ba249-dc2a-454b-b963-b715d699cd4d · outbound
This paper cites Paired regions for shadow detection and removal.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 35(12):2956–2967.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Paired regions for shadow detection and removal.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 35(12):2956–2967
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.137751Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0027b6f6-e4b2-439a-8a3d-5e358bcd63da · outbound
This paper cites Maskshadownet: Toward shadow removal via masked adap- tive instance normalization.IEEE Signal Processing Letters, 28:1699–1703.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Maskshadownet: Toward shadow removal via masked adap- tive instance normalization.IEEE Signal Processing Letters, 28:1699–1703
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.199532Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d4659962-9df9-4f25-a719-4893d067d5bf · outbound
This paper cites Coordinate atten- tion for efficient mobile network design.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Coordinate atten- tion for efficient mobile network design
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.111532Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1b047123-fba2-4122-9817-56039c2758b8 · outbound
This paper cites Revisiting shadow de- tection: A new benchmark dataset for complex world.IEEE Transactions on Image Processing, 30:1925–1938.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Revisiting shadow de- tection: A new benchmark dataset for complex world.IEEE Transactions on Image Processing, 30:1925–1938
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.074606Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c90b63fd-8cf3-437f-870f-303596c66b81 · outbound
This paper cites Unveiling deep shadows: A survey and benchmark on image and video shadow detection, removal, and generation in the deep learning era.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Unveiling deep shadows: A survey and benchmark on image and video shadow detection, removal, and generation in the deep learning era
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T13:55:28.703560Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b5a3d44d-5d89-425a-a3ae-d0576f6a09b1 · outbound
This paper cites Mgrln-net: Mask-guided resid- ual learning network for joint single-image shadow detection and removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Mgrln-net: Mask-guided resid- ual learning network for joint single-image shadow detection and removal
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.185487Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation dba3b45c-99e8-4798-9a61-8117b2a2b571 · outbound
This paper cites an unresolved cited work.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Unresolved cited work
Reference 20
- Resolution
- unresolved
- raw_fallback, observed 2026-05-18T20:22:52.028279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a9fba83b-20b8-4c77-b76a-6991f5bddef7 · outbound
This paper cites Kingma and Jimmy Ba.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Kingma and Jimmy Ba
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.024693Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation af82df53-ac8f-4ccd-9e1b-98bc1740633e · outbound
This paper cites Shadow removal via shadow image decomposition.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Shadow removal via shadow image decomposition
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.109106Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation f5d62eef-3d31-4679-9585-2e8d99c18138 · outbound
This paper cites From shadow segmentation to shadow removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization From shadow segmentation to shadow removal
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.041730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 14888ef0-f24e-4d82-94f3-9748bfff480f · outbound
This paper cites Swinir: Image restoration using swin transformer.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Swinir: Image restoration using swin transformer
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.066505Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 97347fac-b414-4dfb-b93d-0caf667ca9fd · outbound
This paper cites Grid- dehazenet: Attention-based multi-scale network for image dehazing.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Grid- dehazenet: Attention-based multi-scale network for image dehazing
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.241880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c1108a5b-3076-4a27-9379-b3b7b9a72cc2 · outbound
This paper cites Griddehazenet+: An enhanced multi-scale network with intra-task knowledge transfer for single image dehaz- ing.IEEE Transactions on Intelligent Transportation Sys- tems.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Griddehazenet+: An enhanced multi-scale network with intra-task knowledge transfer for single image dehaz- ing.IEEE Transactions on Intelligent Transportation Sys- tems
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.075003Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c40c87f7-2011-4e1a-b06c-4b352c0f1fa1 · outbound
This paper cites Recasting Regional Lighting for Shadow Removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Recasting Regional Lighting for Shadow Removal
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T13:55:28.712323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5eda86e0-97e7-44ee-8853-062f127f4577 · outbound
This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Swin transformer: Hierarchical vision transformer using shifted windows
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.177464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e079955c-cf03-463e-ba5c-4c094b0b1a8a · outbound
This paper cites From shadow generation to shadow removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization From shadow generation to shadow removal
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.230627Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e8a3ff82-7f42-455f-8c15-40e1f977fc9e · outbound
This paper cites A convnet for the 2020s.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization A convnet for the 2020s
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.217856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 60c15973-355e-4626-a2ea-9c2b7f574758 · outbound
This paper cites Hirformer: Dynamic high resolution transformer for large-scale image shadow removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Hirformer: Dynamic high resolution transformer for large-scale image shadow removal
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.061890Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 289bb087-302f-4c3d-a199-acc10c661b82 · outbound
This paper cites an unresolved cited work.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Unresolved cited work
Reference 32
- Resolution
- unresolved
- raw_fallback, observed 2026-05-18T20:22:52.181216Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 8de38f30-86bd-483e-b7b1-2dd2dd3452c7 · outbound
This paper cites Deep multi-scale convolutional neural network for dynamic scene deblurring.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Deep multi-scale convolutional neural network for dynamic scene deblurring
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.053649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 7211e4cf-8272-41b7-883e-1b899641143e · outbound
This paper cites Pytorch: An im- perative style, high-performance deep learning library.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Pytorch: An im- perative style, high-performance deep learning library
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.049722Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 7671c5b2-de79-4a33-87b0-9288a7395fc8 · outbound
This paper cites Ffa-net: Feature fusion attention network for single image dehazing.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Ffa-net: Feature fusion attention network for single image dehazing
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.195565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 36cca572-1bab-43a7-9db0-99e3d994f349 · outbound
This paper cites an unresolved cited work.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Unresolved cited work
Reference 36
- Resolution
- unresolved
- raw_fallback, observed 2026-05-18T20:22:52.224090Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e2724aea-598b-408d-8762-b4116f65ddf8 · outbound
This paper cites U-net: Convolutional networks for biomedical image segmentation.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization U-net: Convolutional networks for biomedical image segmentation
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.236474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6a02ee4c-f0bc-46d7-8488-a5fe14289228 · outbound
This paper cites Molina-Bakhos, Danna Xue, Yixiong Yang, Maria Pilligua, Ramon Baldrich, Maria Vanrell, and Javier Vazquez-Corral.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Molina-Bakhos, Danna Xue, Yixiong Yang, Maria Pilligua, Ramon Baldrich, Maria Vanrell, and Javier Vazquez-Corral
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.087930Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3ffd37b8-c1cd-45d4-a22d-8a335582e246 · outbound
This paper cites Vision transformers for single image dehazing.IEEE Transactions on Image Processing.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Vision transformers for single image dehazing.IEEE Transactions on Image Processing
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.148065Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6db85511-0bd0-4142-8b18-f52eb44adc14 · outbound
This paper cites Wsrd: A novel benchmark for high resolution image shadow removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Wsrd: A novel benchmark for high resolution image shadow removal
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.116236Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation f1a0e868-da57-4be2-b8ae-88cd60b207db · outbound
This paper cites Ntire 2025 ambient lighting normalization challenge report.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Ntire 2025 ambient lighting normalization challenge report
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.107260Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ee1aed96-53a2-456a-a6f2-a20e9e8db70b · outbound
This paper cites Ntire 2026 ambient lighting normaliza- tion challenge report.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Ntire 2026 ambient lighting normaliza- tion challenge report
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.099590Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 97b52f6d-b794-44ac-95d1-7259069f6fd6 · outbound
This paper cites Towards Image Ambient Lighting Normalization.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Towards Image Ambient Lighting Normalization
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T13:55:28.699174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5b63040b-e2a6-40e5-9b3b-46e1a2959678 · outbound
This paper cites Yago Vicente and Dimitris Samaras.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Yago Vicente and Dimitris Samaras
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.103119Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a54feca1-4cb8-4eab-9ded-75e3287c9188 · outbound
This paper cites Stacked conditional generative adversarial networks for jointly learning shadow detection and shadow removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Stacked conditional generative adversarial networks for jointly learning shadow detection and shadow removal
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.143537Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3b446b17-debb-4fac-b0a7-39ec0e09a240 · outbound
This paper cites UniConvNet: Expanding Effective Receptive Field while Maintaining Asymptotically Gaussian Distribution for ConvNets of Any Scale.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization UniConvNet: Expanding Effective Receptive Field while Maintaining Asymptotically Gaussian Distribution for ConvNets of Any Scale
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T13:55:28.708431Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 8a853ec8-f42f-4c17-94b6-89d3c825373a · outbound
This paper cites Bovik, Hamid R.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Bovik, Hamid R
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.152370Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6bf19439-df0b-4f39-b274-79e0e7a8d347 · outbound
This paper cites Homoformer: Homogenized transformer for image shadow removal.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Homoformer: Homogenized transformer for image shadow removal
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.135144Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4ea6f0d6-ffdf-4a4e-8425-cb70fc43858d · outbound
This paper cites Shadow-aware dynamic convolution for shadow removal.Pattern Recognition.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Shadow-aware dynamic convolution for shadow removal.Pattern Recognition
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.167429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 935082f7-f19f-450f-8669-643e7422908c · outbound
This paper cites Towards efficient and scale-robust ultra- high-definition image demoireing.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Towards efficient and scale-robust ultra- high-definition image demoireing
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.173224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation bf2935e1-8698-4727-a494-0ec11b68e7d4 · outbound
This paper cites Restormer: Efficient transformer for high-resolution image restoration.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Restormer: Efficient transformer for high-resolution image restoration
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.139183Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3e3eaf89-375f-432c-9305-fd0748e8dceb · outbound
This paper cites Shadow re- mover: Image shadow removal based on illumination recov- ering optimization.IEEE Transactions on Image Processing, 24(11):4623–4636.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Shadow re- mover: Image shadow removal based on illumination recov- ering optimization.IEEE Transactions on Image Processing, 24(11):4623–4636
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.131032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 952599bb-318e-4cc7-af32-3b3dc6507824 · outbound
This paper cites Efros, Eli Shecht- man, and Oliver Wang.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Efros, Eli Shecht- man, and Oliver Wang
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.165526Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0458f1de-453b-4df3-baf9-63da00697190 · outbound
This paper cites Breaking through the haze: An advanced non-homogeneous dehazing method based on fast fourier convolution and convnext.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Breaking through the haze: An advanced non-homogeneous dehazing method based on fast fourier convolution and convnext
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.164151Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0b7d379d-d971-4876-b6bf-e09cc2d4b345 · outbound
This paper cites Glare: Low light image enhancement via generative latent feature based codebook retrieval.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Glare: Low light image enhancement via generative latent feature based codebook retrieval
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.157744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3d7a392b-3f57-479d-a002-e3fc62bdbf93 · outbound
This paper cites Lita-gs: Illumination- agnostic novel view synthesis via reference-free 3d gaussian splatting and physical priors.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Lita-gs: Illumination- agnostic novel view synthesis via reference-free 3d gaussian splatting and physical priors
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.168972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6994752d-4582-4a1b-b059-37949f1a78bd · outbound
This paper cites Low-light image enhancement via generative perceptual priors.
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization Low-light image enhancement via generative perceptual priors
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T20:22:52.161400Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Pith citing papers
No inbound Pith citation observations are available.