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Paper Citation Record · LEDGER

LAN: Learning to Adapt Noise for Image Denoising

As of 23 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2412.10651.

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

pith.paper-citation-record.v1
2412.10651 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:48:29.733730Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

56 of 56 outbound references displayed

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  • verified fuzzy39
  • unresolved15
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c70fca74-a076-42a8-a079-099c6cfdd22a · outbound

This paper cites an unresolved cited work.

LAN: Learning to Adapt Noise for Image Denoising Unresolved cited work

Reference 1

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Observation 8e3d842f-1fcf-4f65-b5e7-eea68d1a8bfb · outbound

This paper cites Noise flow: Noise modeling with con- ditional normalizing flows.

LAN: Learning to Adapt Noise for Image Denoising Noise flow: Noise modeling with con- ditional normalizing flows

Reference 2

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Observation 916ab4ca-7f03-40a4-92e1-db16da10f221 · outbound

This paper cites Ntire 2020 challenge on real image denoising: Dataset, methods and results.

LAN: Learning to Adapt Noise for Image Denoising Ntire 2020 challenge on real image denoising: Dataset, methods and results

Reference 3

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Observation 10288515-cb45-4de4-8356-554ed31e4070 · outbound

This paper cites Renoir–a dataset for real low-light image noise reduction.

LAN: Learning to Adapt Noise for Image Denoising Renoir–a dataset for real low-light image noise reduction

Reference 4

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Observation c02f4d22-faac-4e4b-9caa-ec91fb958287 · outbound

This paper cites Real image denoising with feature attention.

LAN: Learning to Adapt Noise for Image Denoising Real image denoising with feature attention

Reference 5

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Observation 0fea61c9-5f46-4d65-be9b-0c2e65198f89 · outbound

This paper cites Noise2self: Blind denoising by self-supervision.

LAN: Learning to Adapt Noise for Image Denoising Noise2self: Blind denoising by self-supervision

Reference 6

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Observation 430b7618-2a67-4344-96b6-461cbeaee34a · outbound

This paper cites A non-local algorithm for image denoising.

LAN: Learning to Adapt Noise for Image Denoising A non-local algorithm for image denoising

Reference 7

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Source-reported events for the cited work

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Observation bfcf50e1-0557-4671-a379-8a40ddf0a635 · outbound

This paper cites Towards evaluating the robustness of neural networks.

LAN: Learning to Adapt Noise for Image Denoising Towards evaluating the robustness of neural networks

Reference 8

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Source-reported events for the cited work

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Observation 6f0e77db-a02c-4158-81eb-1aa3dcd5e361 · outbound

This paper cites Learn- ing camera-aware noise models.

LAN: Learning to Adapt Noise for Image Denoising Learn- ing camera-aware noise models

Reference 9

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Source-reported events for the cited work

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Observation c79b5fe6-285a-4f7e-8a9a-5db7ce23948d · outbound

This paper cites Pre-trained image processing transformer.

LAN: Learning to Adapt Noise for Image Denoising Pre-trained image processing transformer

Reference 10

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Source-reported events for the cited work

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Observation 15efe3a0-db7e-44d9-b505-12b29216191e · outbound

This paper cites Hinet: Half instance normalization network for image restoration.

LAN: Learning to Adapt Noise for Image Denoising Hinet: Half instance normalization network for image restoration

Reference 11

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Source-reported events for the cited work

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Observation fae750da-f4a5-4e7c-86c1-e9da75ccafb4 · outbound

This paper cites Image denoising by sparse 3-d transform- domain collaborative filtering.

LAN: Learning to Adapt Noise for Image Denoising Image denoising by sparse 3-d transform- domain collaborative filtering

Reference 12

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verified fuzzy
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Source-reported events for the cited work

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Observation c56d38d8-b478-40d2-827e-597678f4357a · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

LAN: Learning to Adapt Noise for Image Denoising An image is worth 16x16 words: Transformers for image recognition at scale

Reference 13

Resolution
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Observation 41e70490-df21-4fd0-af2c-eb684254de96 · outbound

This paper cites Model- agnostic meta-learning for fast adaptation of deep networks.

LAN: Learning to Adapt Noise for Image Denoising Model- agnostic meta-learning for fast adaptation of deep networks

Reference 14

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Source-reported events for the cited work

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Observation 44e6b9f3-81e3-4756-b621-96eafe42b0e3 · outbound

This paper cites Generative adversarial nets.

LAN: Learning to Adapt Noise for Image Denoising Generative adversarial nets

Reference 15

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Observation b16b0fed-b1d5-46d1-b095-67afd1a0f495 · outbound

This paper cites Test-time Adaptation for Real Image Denoising via Meta-transfer Learning.

LAN: Learning to Adapt Noise for Image Denoising Test-time Adaptation for Real Image Denoising via Meta-transfer Learning

Reference 16

Resolution
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Observation cdd55c0a-2bd2-4093-9101-968d2ac07021 · outbound

This paper cites Neighbor2neighbor: Self-supervised de- noising from single noisy images.

LAN: Learning to Adapt Noise for Image Denoising Neighbor2neighbor: Self-supervised de- noising from single noisy images

Reference 17

Resolution
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Observation 0e0d2751-db94-41c2-ba3e-eca3b6abaf8c · outbound

This paper cites Neighbor2neighbor: Self-supervised de- noising from single noisy images.

LAN: Learning to Adapt Noise for Image Denoising Neighbor2neighbor: Self-supervised de- noising from single noisy images

Reference 18

Resolution
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Source-reported events for the cited work

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Observation ad95f00e-dba2-4b51-89b9-a4c5ee11f4ed · outbound

This paper cites Image-to-image translation with conditional adver- sarial networks.

LAN: Learning to Adapt Noise for Image Denoising Image-to-image translation with conditional adver- sarial networks

Reference 19

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Observation c38fd3f0-2288-4477-9718-dc631717ebd7 · outbound

This paper cites C2n: Practical generative noise modeling for real-world denoising.

LAN: Learning to Adapt Noise for Image Denoising C2n: Practical generative noise modeling for real-world denoising

Reference 20

Resolution
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Source-reported events for the cited work

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Observation e263e0fc-85b6-435e-9104-0c218eef7acc · outbound

This paper cites Adam: A Method for Stochastic Optimization.

LAN: Learning to Adapt Noise for Image Denoising Adam: A Method for Stochastic Optimization

Reference 21

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Source-reported events for the cited work

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Observation 20547fe0-10c2-47be-a014-5f58b18b1295 · outbound

This paper cites Auto-Encoding Variational Bayes.

LAN: Learning to Adapt Noise for Image Denoising Auto-Encoding Variational Bayes

Reference 22

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Observation 364cd0d4-1ccc-49a2-9caa-8cee9a2d2587 · outbound

This paper cites Modeling srgb camera noise with normal- izing flows.

LAN: Learning to Adapt Noise for Image Denoising Modeling srgb camera noise with normal- izing flows

Reference 23

Resolution
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Source-reported events for the cited work

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Observation 330dd142-c74c-4419-83b2-e3cb25dc81ee · outbound

This paper cites Noise2void-learning denoising from single noisy images.

LAN: Learning to Adapt Noise for Image Denoising Noise2void-learning denoising from single noisy images

Reference 24

Resolution
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Source-reported events for the cited work

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Observation a25cf717-8429-4503-8c97-57c2265ff90c · outbound

This paper cites Universal source-free domain adaptation.

LAN: Learning to Adapt Noise for Image Denoising Universal source-free domain adaptation

Reference 25

Resolution
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Source-reported events for the cited work

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Observation 56f4f814-2a05-49d9-a86a-47c1107f025a · outbound

This paper cites Diverse image-to-image translation via disentangled representations.

LAN: Learning to Adapt Noise for Image Denoising Diverse image-to-image translation via disentangled representations

Reference 26

Resolution
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Source-reported events for the cited work

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Observation 6f737e51-2cbc-44fc-a96f-c743d1dd7de4 · outbound

This paper cites Noisetransfer: Image noise generation with contrastive embeddings.

LAN: Learning to Adapt Noise for Image Denoising Noisetransfer: Image noise generation with contrastive embeddings

Reference 27

Resolution
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Source-reported events for the cited work

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Observation 01158c49-effe-4fa1-a33c-cc239280e8ba · outbound

This paper cites Self-Supervised Fast Adaptation for Denoising via Meta-Learning.

LAN: Learning to Adapt Noise for Image Denoising Self-Supervised Fast Adaptation for Denoising via Meta-Learning

Reference 28

Resolution
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Source-reported events for the cited work

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Observation 6e00e87f-0568-4fda-8f7a-f15469997f7a · outbound

This paper cites Ap-bsn: Self-supervised denoising for real-world images via asym- metric pd and blind-spot network.

LAN: Learning to Adapt Noise for Image Denoising Ap-bsn: Self-supervised denoising for real-world images via asym- metric pd and blind-spot network

Reference 29

Resolution
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Source-reported events for the cited work

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Observation 6b844fec-a0dc-4cb3-ab91-227d92d7d6a5 · outbound

This paper cites Noise2noise: Learning image restoration without clean data.

LAN: Learning to Adapt Noise for Image Denoising Noise2noise: Learning image restoration without clean data

Reference 30

Resolution
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Source-reported events for the cited work

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Observation b279cb14-c309-4cf9-84c3-cc0f9a9ba720 · outbound

This paper cites Swinir: Image restoration us- ing swin transformer.

LAN: Learning to Adapt Noise for Image Denoising Swinir: Image restoration us- ing swin transformer

Reference 31

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Source-reported events for the cited work

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Observation 83218175-a242-4747-b38e-13dd065c062e · outbound

This paper cites Unsupervised image-to-image translation networks.

LAN: Learning to Adapt Noise for Image Denoising Unsupervised image-to-image translation networks

Reference 32

Resolution
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Source-reported events for the cited work

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Observation 82295786-d90d-4b13-8fe1-ee1f62232cc0 · outbound

This paper cites Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency.

LAN: Learning to Adapt Noise for Image Denoising Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency

Reference 33

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Source-reported events for the cited work

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Observation 5623c847-3d10-482a-8824-45641dcbc987 · outbound

This paper cites Non-local sparse models for image restoration.

LAN: Learning to Adapt Noise for Image Denoising Non-local sparse models for image restoration

Reference 34

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 621dbf98-1a24-427e-8f37-6d1aea820019 · outbound

This paper cites Zero-shot noise2noise: Efficient image denoising without any data.

LAN: Learning to Adapt Noise for Image Denoising Zero-shot noise2noise: Efficient image denoising without any data

Reference 35

Resolution
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Source-reported events for the cited work

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Observation 0c1a30e7-0611-4e57-b9bf-7b6292553f39 · outbound

This paper cites A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics.

LAN: Learning to Adapt Noise for Image Denoising A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.596386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 0af76fc3-64ee-488f-8375-6355051fc41b · outbound

This paper cites A holistic approach to cross-channel im- age noise modeling and its application to image denoising.

LAN: Learning to Adapt Noise for Image Denoising A holistic approach to cross-channel im- age noise modeling and its application to image denoising

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.577475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.272426Z digest=sha256:38a60409561be39d35387344b1fac20f3bc78aad309992fc0985b1da93bd8c8e

Observation 049d7a8c-1c8c-4281-ba74-34057e905469 · outbound

This paper cites On First-Order Meta-Learning Algorithms.

LAN: Learning to Adapt Noise for Image Denoising On First-Order Meta-Learning Algorithms

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:29.278419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:29.278419Z digest=sha256:6fab0277be3af0935a70fbf8a261e433f60108920b5c4aa0b19375e85c597780

Observation 8a5e4f31-33b8-4e6e-8a55-75ff5cf7c115 · outbound

This paper cites Benchmarking denoising al- gorithms with real photographs.

LAN: Learning to Adapt Noise for Image Denoising Benchmarking denoising al- gorithms with real photographs

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.557492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.284287Z digest=sha256:7aff29afbb0ad98c5d25ee6418bbf3b929ca4f37be6b9d572c35d686c11a33a3

Observation ff3cc57a-f7db-471b-90d0-d362a4f0c70b · outbound

This paper cites Self2self with dropout: Learning self-supervised denoising from single image.

LAN: Learning to Adapt Noise for Image Denoising Self2self with dropout: Learning self-supervised denoising from single image

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.538557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.289442Z digest=sha256:7b43033e8bffe353709c20509188a2d81ae78c48ff8f78b21f9b811ec182bd1b

Observation 874e47d6-fb49-4c10-8b5e-0b720e67186f · outbound

This paper cites Nonlinear total variation based noise removal algorithms.

LAN: Learning to Adapt Noise for Image Denoising Nonlinear total variation based noise removal algorithms

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.519484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.294771Z digest=sha256:02beca9a894c8bdcd6da85c9a959dfc33f581cd8faf0e0a65cd91315785c9d9b

Observation 9893ebc2-16bb-49d0-b64d-c43668b9fce4 · outbound

This paper cites Intriguing properties of neural networks.

LAN: Learning to Adapt Noise for Image Denoising Intriguing properties of neural networks

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:29.328668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:29.328668Z digest=sha256:5569ed996b290aa352315dd5de64afbed31d466818db39c754238e9bf6ca09af

Observation 98aad6a7-c699-4cf4-b98c-cfef060cc0ea · outbound

This paper cites Deep image prior.

LAN: Learning to Adapt Noise for Image Denoising Deep image prior

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:29.382900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:29.382900Z digest=sha256:66263b2e46195319f16b2d0ac0d3f6b0f4a390c5ed248f273669ffd9b6e2c774

Observation f55e0452-7087-47bc-9e46-ed5384dd5ec0 · outbound

This paper cites Tent: Fully test-time adaptation by entropy minimization.

LAN: Learning to Adapt Noise for Image Denoising Tent: Fully test-time adaptation by entropy minimization

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.372210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.452914Z digest=sha256:fff915e34d66f52490c0cfd8a69c12e6fdfc520fff911d245be7b820960bc4b3

Observation 5f5f7758-f867-42d4-9f2a-38adc97cd317 · outbound

This paper cites Noise2info: Noisy image to information of noise for self-supervised image denoising.

LAN: Learning to Adapt Noise for Image Denoising Noise2info: Noisy image to information of noise for self-supervised image denoising

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.296096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.485697Z digest=sha256:612a824feb627d8ee5a16b9553aa027c682be9be9228e71a16358af634097fa0

Observation a24ffde9-5cbd-4b1d-b9a6-44c229aac41d · outbound

This paper cites Uformer: A gen- eral u-shaped transformer for image restoration.

LAN: Learning to Adapt Noise for Image Denoising Uformer: A gen- eral u-shaped transformer for image restoration

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:29.491190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:29.491190Z digest=sha256:3ac71e11b45f2a11d1bb7e0a846adb4af5547808a8614aa2c657788805b3c7c3

Observation e6b9d09f-7878-4762-8e08-d98cfa011ba2 · outbound

This paper cites Image denoising and inpainting with deep neural networks.

LAN: Learning to Adapt Noise for Image Denoising Image denoising and inpainting with deep neural networks

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.265038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.496812Z digest=sha256:2693fa6ee5ac933028dc0da3c2143393d4706e3696f075a14a59e6c084f2b6da

Observation 7ccdd61b-2d8f-4777-9fbc-126270da9083 · outbound

This paper cites Real-world Noisy Image Denoising: A New Benchmark.

LAN: Learning to Adapt Noise for Image Denoising Real-world Noisy Image Denoising: A New Benchmark

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:29.502027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:29.502027Z digest=sha256:609157b1d440f82138c791a2f57a573be7a5f8d3f9174b12811f34d9dffe5d44

Observation 8d25eedb-9e2e-4320-a36b-9e361ad42b08 · outbound

This paper cites Generalized source-free domain adaptation.

LAN: Learning to Adapt Noise for Image Denoising Generalized source-free domain adaptation

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.246879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.507039Z digest=sha256:e745e683f1f0ae30ea4910d3a0d21738a753bcf8261d76b24bdc431657057cec

Observation 5bcd1c70-470a-44a6-ac0e-3bb4513b8a07 · outbound

This paper cites Dual adversarial network: Toward real-world noise removal and noise generation.

LAN: Learning to Adapt Noise for Image Denoising Dual adversarial network: Toward real-world noise removal and noise generation

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.227441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.512234Z digest=sha256:8860394eee38f6f651d722002a2523adb9339e6504d553397fd7f419ee7f7ad9

Observation 227ba1b7-db05-42ed-8b18-9c3d44016107 · outbound

This paper cites Cycleisp: Real image restoration via improved data synthesis.

LAN: Learning to Adapt Noise for Image Denoising Cycleisp: Real image restoration via improved data synthesis

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.207939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.517830Z digest=sha256:ae24f59434db206419ec57bbe6ec0675deebce755ada9c15c5e1c5c4cd9616a0

Observation fb1b6e7f-c727-4d6e-9dec-3d9e49346b7f · outbound

This paper cites Learning enriched features for real image restoration and enhancement.

LAN: Learning to Adapt Noise for Image Denoising Learning enriched features for real image restoration and enhancement

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.189920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.523343Z digest=sha256:8c5aa62774b384a1666d5dbffbff6be456bea4d7c5cfa526915e30bd3b2049e4

Observation af1861da-a137-40a3-871d-c60ceaf73398 · outbound

This paper cites Restormer: Efficient transformer for high-resolution image restoration.

LAN: Learning to Adapt Noise for Image Denoising Restormer: Efficient transformer for high-resolution image restoration

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.171009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.528836Z digest=sha256:74a7701f6e90481ad286da2484724899a39805b830e5b72ee10d9efc824e57cc

Observation 3fd74a42-3b64-48fb-879c-248eed067fa2 · outbound

This paper cites Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising.

LAN: Learning to Adapt Noise for Image Denoising Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.150573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.590647Z digest=sha256:8372a64af0fdf17afe9b0b31e310c5b4dca8c0abe7694e2d730999b5013f1fef

Observation 9ad95125-225d-452d-acb7-c1378c746e9d · outbound

This paper cites Ffdnet: Toward a fast and flexible solution for cnn-based image denoising.

LAN: Learning to Adapt Noise for Image Denoising Ffdnet: Toward a fast and flexible solution for cnn-based image denoising

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:29.668603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:29.668603Z digest=sha256:3ae89ae56ae24f3b789e39fb37d76402cff328bc86a30dd2c3c9d5ae6aff3aeb

Observation f156d310-34ed-4f96-b654-a526f0180948 · outbound

This paper cites To- ward multimodal image-to-image translation.

LAN: Learning to Adapt Noise for Image Denoising To- ward multimodal image-to-image translation

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:30.118216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T15:48:29.733730Z digest=sha256:a18d08fde126a1076b5c74e15afbe50d3648d276948ffb658fd7bf8876e1a307

Pith citing papers

No inbound Pith citation observations are available.