Paper Citation Record · LEDGER

MSSIDD: A Benchmark for Multi-Sensor Denoising

As of 24 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 2 inbound Pith citation observations for arXiv:2411.11562.

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

pith.paper-citation-record.v1
2411.11562 v1

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:28:26.142831Z

measured 68 of 68 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:01:38.693131Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T21:22:09.765205Z

Reference resolution

66 of 66 outbound references displayed

verified exact1
verified fuzzy61
unresolved4
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d506de3f-ddf9-4786-b549-465216e245c1 · outbound

This paper cites https:// www.sony-semicon.com/en/products/is/ camera/index.html.

MSSIDD: A Benchmark for Multi-Sensor Denoising https:// www.sony-semicon.com/en/products/is/ camera/index.html

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.800306Z

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

Observation 23315353-6317-440f-bde3-2553c53c7d17 · outbound

This paper cites https://en.wikipedia.

MSSIDD: A Benchmark for Multi-Sensor Denoising https://en.wikipedia

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.783620Z

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.

Observation 254dd72b-a1ad-49e3-b426-b61922386f88 · outbound

This paper cites A high-quality denoising dataset for smartphone cameras.

MSSIDD: A Benchmark for Multi-Sensor Denoising A high-quality denoising dataset for smartphone cameras

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.695716Z

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.

Observation 1b8fd4cc-78c0-4a22-823a-42e38de7dd7d · outbound

This paper cites Cross-camera con- volutional color constancy.

MSSIDD: A Benchmark for Multi-Sensor Denoising Cross-camera con- volutional color constancy

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.652264Z

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.

Observation fd1350c8-9de8-443f-9127-e87f477c9af3 · outbound

This paper cites Real image denoising with feature attention.

MSSIDD: A Benchmark for Multi-Sensor Denoising Real image denoising with feature attention

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.636047Z

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.

Observation 9cb0ec8c-ac2a-4bb1-893f-0ae74b4a0549 · outbound

This paper cites Invariant Risk Minimization.

MSSIDD: A Benchmark for Multi-Sensor Denoising Invariant Risk Minimization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T18:28:25.149476Z

Source-reported events for the cited work

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Observation b3bedc1d-f571-4c0a-ac50-65b2e0c987c2 · outbound

This paper cites Convolutional color constancy.

MSSIDD: A Benchmark for Multi-Sensor Denoising Convolutional color constancy

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.619622Z

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.

Observation 8289c932-df03-4769-86f7-6522fa307633 · outbound

This paper cites Photon shot noise.

MSSIDD: A Benchmark for Multi-Sensor Denoising Photon shot noise

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.603942Z

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.

Observation bc62411b-254b-4fef-8335-4b7e68d5d6a8 · outbound

This paper cites Automatic exposure algorithms for digital photography.

MSSIDD: A Benchmark for Multi-Sensor Denoising Automatic exposure algorithms for digital photography

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.516442Z

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.

Observation a2b5fbeb-b56f-43e1-a56a-2f8553136469 · outbound

This paper cites Boie and Ingemar J.

MSSIDD: A Benchmark for Multi-Sensor Denoising Boie and Ingemar J

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.469441Z

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.

Observation 1a08db4b-5253-4b0f-824b-549be17a98ac · outbound

This paper cites Unpro- cessing images for learned raw denoising.

MSSIDD: A Benchmark for Multi-Sensor Denoising Unpro- cessing images for learned raw denoising

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.452677Z

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.

Observation 9e71af71-801e-478f-87d1-51dbeb8d661d · outbound

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

MSSIDD: A Benchmark for Multi-Sensor Denoising A non-local algorithm for image denoising

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.436464Z

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.

Observation d0d64238-44dd-4d57-b099-a707bae9dd93 · outbound

This paper cites Self-similarity driven color demo- saicking.

MSSIDD: A Benchmark for Multi-Sensor Denoising Self-similarity driven color demo- saicking

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.420377Z

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.

Observation 6e9ad0ec-cf9d-4568-bde2-533701422931 · outbound

This paper cites Learning camera-aware noise models.

MSSIDD: A Benchmark for Multi-Sensor Denoising Learning camera-aware noise models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.404421Z

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.

Observation ff8a5806-eba5-40e8-8773-9c2fd61e84db · outbound

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

MSSIDD: A Benchmark for Multi-Sensor Denoising Hinet: Half instance normalization network for image restoration

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.388259Z

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.

Observation de5e3d83-7824-4bb1-820f-b53d317d8877 · outbound

This paper cites Simple baselines for image restoration.

MSSIDD: A Benchmark for Multi-Sensor Denoising Simple baselines for image restoration

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.239276Z

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.

Observation 853733a7-3b03-4b5d-bf61-4d63143678c9 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

MSSIDD: A Benchmark for Multi-Sensor Denoising A simple framework for contrastive learning of visual representations

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.223312Z

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.

Observation 4afb3a44-0b13-41ea-96f0-58eef9c438c5 · outbound

This paper cites Intrinsic phase-preserving networks for depth super resolution.

MSSIDD: A Benchmark for Multi-Sensor Denoising Intrinsic phase-preserving networks for depth super resolution

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.207728Z

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.

Observation 9424fa20-93ef-48ac-b3d4-c0a8e305d21b · outbound

This paper cites Focal network for image restoration.

MSSIDD: A Benchmark for Multi-Sensor Denoising Focal network for image restoration

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.190649Z

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.

Observation 07502953-ab31-46cd-969a-00e9448ff4e6 · outbound

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

MSSIDD: A Benchmark for Multi-Sensor Denoising Image denoising by sparse 3-d transform-domain collaborative filtering

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.174792Z

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.

Observation c7e8ea2a-8ad5-4032-bd79-4c1c852ea591 · outbound

This paper cites Unsupervised domain adaptation by backpropagation.

MSSIDD: A Benchmark for Multi-Sensor Denoising Unsupervised domain adaptation by backpropagation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.157723Z

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.

Observation 1e725ae7-09f6-4bd6-853a-8d4bef6e5cfd · outbound

This paper cites Malvar-he-cutler linear image demo- saicking.

MSSIDD: A Benchmark for Multi-Sensor Denoising Malvar-he-cutler linear image demo- saicking

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.140125Z

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.

Observation 4166d48a-8719-4005-b821-7b4811b8075d · outbound

This paper cites Deep joint demosaicking and denoising.

MSSIDD: A Benchmark for Multi-Sensor Denoising Deep joint demosaicking and denoising

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.123563Z

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.

Observation 83209e41-a506-4a4f-8001-a59ff1d54ee9 · outbound

This paper cites Weighted nuclear norm minimization with application to image denoising.

MSSIDD: A Benchmark for Multi-Sensor Denoising Weighted nuclear norm minimization with application to image denoising

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:28.107640Z

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.

Observation 48a2df65-bca7-4d2c-87cd-d7a1ccf4285f · outbound

This paper cites Gamma correction for digital fringe projection profilometry.

MSSIDD: A Benchmark for Multi-Sensor Denoising Gamma correction for digital fringe projection profilometry

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.974514Z

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.

Observation e1123cdf-2e88-4829-942f-b43c4e43fb00 · outbound

This paper cites Toward convolutional blind denoising of 9 real photographs.

MSSIDD: A Benchmark for Multi-Sensor Denoising Toward convolutional blind denoising of 9 real photographs

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.926175Z

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.

Observation fef5010b-ea26-4718-8520-2188d3f70d63 · outbound

This paper cites Radiometric ccd camera calibration and noise estimation.

MSSIDD: A Benchmark for Multi-Sensor Denoising Radiometric ccd camera calibration and noise estimation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.909622Z

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.

Observation 16b76c2b-820b-48db-a11d-61af8208380d · outbound

This paper cites The human condition as seen from the cross: Luther and disability.

MSSIDD: A Benchmark for Multi-Sensor Denoising The human condition as seen from the cross: Luther and disability

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.893564Z

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.

Observation a50c2a20-8803-44b1-a764-7330335a12aa · outbound

This paper cites Adaptive homogeneity-directed demosaicing algorithm.

MSSIDD: A Benchmark for Multi-Sensor Denoising Adaptive homogeneity-directed demosaicing algorithm

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.878395Z

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.

Observation d572e1a7-bc26-4003-8ab0-254573a64c30 · outbound

This paper cites Focnet: A fractional optimal control network for image denoising.

MSSIDD: A Benchmark for Multi-Sensor Denoising Focnet: A fractional optimal control network for image denoising

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.861556Z

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.

Observation 080a7fd6-2d3d-4a83-83bc-b1e726aa1a08 · outbound

This paper cites Lighting every darkness in two pairs: A calibration-free pipeline for raw denoising.

MSSIDD: A Benchmark for Multi-Sensor Denoising Lighting every darkness in two pairs: A calibration-free pipeline for raw denoising

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.807392Z

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.

Observation 7424cf9d-1f4b-4a3a-ab16-82a1823bf78e · outbound

This paper cites Transfer learning from synthetic to real- noise denoising with adaptive instance normalization.

MSSIDD: A Benchmark for Multi-Sensor Denoising Transfer learning from synthetic to real- noise denoising with adaptive instance normalization

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.718111Z

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.

Observation a68d3565-b39d-491b-93ac-0e12edafacc0 · outbound

This paper cites Efficient visual computing with camera raw snapshots.

MSSIDD: A Benchmark for Multi-Sensor Denoising Efficient visual computing with camera raw snapshots

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.701129Z

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.

Observation 3e46556e-a03b-476b-ae6f-289b1bea24e4 · outbound

This paper cites Swinir: Image restoration using swin transformer.

MSSIDD: A Benchmark for Multi-Sensor Denoising Swinir: Image restoration using swin transformer

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.685512Z

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.

Observation 7ebe0b52-512a-49f8-b9d0-b4b66a5c7b26 · outbound

This paper cites Non-local recurrent network for image restoration.

MSSIDD: A Benchmark for Multi-Sensor Denoising Non-local recurrent network for image restoration

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.669297Z

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.

Observation 31c69861-38d4-4195-b1ca-8f790bdfdb83 · outbound

This paper cites Decoupled weight decay regularization.

MSSIDD: A Benchmark for Multi-Sensor Denoising Decoupled weight decay regularization

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.653985Z

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.

Observation d6c15158-ec7f-4d4b-aaab-1ee791e54a50 · outbound

This paper cites Visu- alizing data using t-sne.

MSSIDD: A Benchmark for Multi-Sensor Denoising Visu- alizing data using t-sne

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.562435Z

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.

Observation 8b2ff91b-0367-403f-9a51-279aa637038b · outbound

This paper cites Towards bridging sample complexity and model capacity.

MSSIDD: A Benchmark for Multi-Sensor Denoising Towards bridging sample complexity and model capacity

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.453681Z

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.

Observation e4118681-3e96-43a0-8e2a-3bd55e77217a · outbound

This paper cites Exploring and utilizing pattern imbal- ance.

MSSIDD: A Benchmark for Multi-Sensor Denoising Exploring and utilizing pattern imbal- ance

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.438268Z

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.

Observation 6cc38414-0daa-4d49-a77e-d92898703225 · outbound

This paper cites Graphical modeling for multi-source domain adaptation.

MSSIDD: A Benchmark for Multi-Sensor Denoising Graphical modeling for multi-source domain adaptation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.419714Z

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.

Observation 3c650031-96f8-496c-89fc-9a58e867e9a7 · outbound

This paper cites Reducing Domain Gap by Reducing Style Bias.

MSSIDD: A Benchmark for Multi-Sensor Denoising Reducing Domain Gap by Reducing Style Bias

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T18:28:25.708612Z

Source-reported events for the cited work

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Observation b8f9745f-0ac9-429f-ae0c-383aa610287b · outbound

This paper cites An iterative regularization method for total variation-based image restoration.

MSSIDD: A Benchmark for Multi-Sensor Denoising An iterative regularization method for total variation-based image restoration

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.290110Z

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.

Observation abd30418-54e2-4bc1-be50-dcaad7224dd1 · outbound

This paper cites Gradient based threshold free color filter array interpolation.

MSSIDD: A Benchmark for Multi-Sensor Denoising Gradient based threshold free color filter array interpolation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.172666Z

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.

Observation c8464f4e-aec3-4e8c-9ae4-c761b4512ae9 · outbound

This paper cites Benchmarking denoising algorithms with real photographs.

MSSIDD: A Benchmark for Multi-Sensor Denoising Benchmarking denoising algorithms with real photographs

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.156658Z

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.

Observation 331324a1-722d-4cb6-af25-d9e87fd46bc5 · outbound

This paper cites Demosaicking methods for bayer color arrays.

MSSIDD: A Benchmark for Multi-Sensor Denoising Demosaicking methods for bayer color arrays

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.139159Z

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.

Observation 579275d6-cd83-4b67-a9dc-6e307322fe0e · outbound

This paper cites U-net: Convolutional networks for biomedical im- age segmentation.

MSSIDD: A Benchmark for Multi-Sensor Denoising U-net: Convolutional networks for biomedical im- age segmentation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.122597Z

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.

Observation 73105119-b780-4671-a8ff-5661e4ba9bd3 · outbound

This paper cites Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization.

MSSIDD: A Benchmark for Multi-Sensor Denoising Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T18:28:25.742235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb17f37c-b5a2-48ac-81e5-f73cf7e56786 · outbound

This paper cites Ntire 2017 challenge on single image super-resolution: Methods and results.

MSSIDD: A Benchmark for Multi-Sensor Denoising Ntire 2017 challenge on single image super-resolution: Methods and results

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.104434Z

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.

Observation 43f76bf5-5563-41a3-9125-d6c6faceb8c0 · outbound

This paper cites Attention is all you need.

MSSIDD: A Benchmark for Multi-Sensor Denoising Attention is all you need

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.086572Z

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.

Observation 3434b9c7-1719-49de-b5f0-22ca2064a63b · outbound

This paper cites Omni aggregation networks for lightweight image super-resolution.

MSSIDD: A Benchmark for Multi-Sensor Denoising Omni aggregation networks for lightweight image super-resolution

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:27.069692Z

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.

Observation a32cc76c-4bbf-45ed-852e-2834c2ce3a0d · outbound

This paper cites Practical deep raw image denoising on mobile devices.

MSSIDD: A Benchmark for Multi-Sensor Denoising Practical deep raw image denoising on mobile devices

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.959061Z

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.

Observation 5bd46e07-d530-40f2-98af-cf6ad3a17010 · outbound

This paper cites Bovik, H.R.

MSSIDD: A Benchmark for Multi-Sensor Denoising Bovik, H.R

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.865843Z

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.

Observation 9d2f4f74-13e9-4f4d-a074-6d9cb1fab04c · outbound

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

MSSIDD: A Benchmark for Multi-Sensor Denoising Uformer: A general u-shaped transformer for image restoration

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.849530Z

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.

Observation 6b6968e1-ea1c-4ad4-a545-f19386fe8cd8 · outbound

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

MSSIDD: A Benchmark for Multi-Sensor Denoising Learning enriched features for real image restoration and enhancement

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.833381Z

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.

Observation 3568f519-aa33-48af-9b1f-3a4da80c953f · outbound

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

MSSIDD: A Benchmark for Multi-Sensor Denoising Cycleisp: Real image restoration via improved data synthesis

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.816816Z

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.

Observation 8cb50372-c7ee-49cb-934c-7df2a927bc81 · outbound

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

MSSIDD: A Benchmark for Multi-Sensor Denoising Learning enriched features for real image restoration and enhancement

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.800839Z

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.

Observation c450c020-9003-4d94-9790-2057dbfa1215 · outbound

This paper cites Multi-stage progressive image restora- tion.

MSSIDD: A Benchmark for Multi-Sensor Denoising Multi-stage progressive image restora- tion

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.784976Z

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.

Observation 88be8cae-e15c-488e-b022-181b6b0d45a6 · outbound

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

MSSIDD: A Benchmark for Multi-Sensor Denoising Restormer: Efficient transformer for high- resolution image restoration

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.768296Z

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.

Observation 5a072e94-5faa-44b3-b6ed-d41cc690ab16 · outbound

This paper cites Ingredient-oriented multi-degradation learning for image restoration.

MSSIDD: A Benchmark for Multi-Sensor Denoising Ingredient-oriented multi-degradation learning for image restoration

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.750269Z

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.

Observation a1502bff-80c2-45ff-b220-be40dfbd3ce4 · outbound

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

MSSIDD: A Benchmark for Multi-Sensor Denoising Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.732153Z

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.

Observation 61449385-01dc-4a8d-8e51-cf1dcbd2f8f3 · outbound

This paper cites Learning deep cnn denoiser prior for image restoration.

MSSIDD: A Benchmark for Multi-Sensor Denoising Learning deep cnn denoiser prior for image restoration

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.681408Z

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.

Observation eccc5e3a-c104-4223-9cab-be1a447c7757 · outbound

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

MSSIDD: A Benchmark for Multi-Sensor Denoising Ffdnet: Toward a fast and flexible solution for cnn-based image denoising

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.576830Z

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.

Observation bf84f116-4b25-4a95-9cd8-56d1f2151b56 · outbound

This paper cites Plug-and-play image restoration with deep denoiser prior.

MSSIDD: A Benchmark for Multi-Sensor Denoising Plug-and-play image restoration with deep denoiser prior

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.401101Z

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.

Observation 4a06661f-25cb-4782-8076-848f16f2b5a3 · outbound

This paper cites Variational adversar- ial defense: A bayes perspective for adversarial train- ing.

MSSIDD: A Benchmark for Multi-Sensor Denoising Variational adversar- ial defense: A bayes perspective for adversarial train- ing

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:28:26.384431Z

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.

Observation bacafc5f-8917-4398-9d10-4e8c59e8d4b1 · outbound

This paper cites an unresolved cited work.

MSSIDD: A Benchmark for Multi-Sensor Denoising Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-12T18:28:26.367210Z

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.

Observation 5acc2677-75f1-4445-9f86-faf033e1ff05 · outbound

This paper cites meta data.pkl.

MSSIDD: A Benchmark for Multi-Sensor Denoising meta data.pkl

Reference 66

Resolution: verified exact; raw_fallback, observed 2026-08-12T18:28:26.295434Z

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.

Pith citing papers

Observation ef5a1702-5b09-4794-8071-70e74d183600 · inbound

Q-Agent: Quality-Driven Chain-of-Thought Image Restoration Agent through Robust Multimodal Large Language Model cites this paper.

Q-Agent: Quality-Driven Chain-of-Thought Image Restoration Agent through Robust Multimodal Large Language Model MSSIDD: A Benchmark for Multi-Sensor Denoising

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-22T21:22:09.768088Z

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.

Observation fc249f86-bb9e-4169-b426-df1f88ff3b4b · inbound

GeoMM: On Geodesic Perspective for Multi-modal Learning cites this paper.

GeoMM: On Geodesic Perspective for Multi-modal Learning MSSIDD: A Benchmark for Multi-Sensor Denoising

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T21:01:38.693131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.