Paper Citation Record · LEDGER

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration

As of 23 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 3 inbound Pith citation observations for arXiv:2412.01427.

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

pith.paper-citation-record.v1
2412.01427 v1

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:28:48.191753Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:12:27.858181Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T23:34:51.606457Z

Reference resolution

64 of 64 outbound references displayed

verified exact1
verified fuzzy49
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6357a235-e95f-481e-8485-91dc412c4fc9 · outbound

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

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration A high-quality denoising dataset for smartphone cameras

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.255789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 19266a0e-cc13-4ae8-80e9-c52875a6016d · outbound

This paper cites GPT-4 Technical Report.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration GPT-4 Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:47.884763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40153d06-b6a7-4f11-85cc-959f8a2bf8b3 · outbound

This paper cites Multimodal prompt perceiver: Empower adap- tiveness generalizability and fidelity for all-in-one image restoration.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Multimodal prompt perceiver: Empower adap- tiveness generalizability and fidelity for all-in-one image restoration

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.240868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 64f04ca6-a97d-4fde-ae8a-9bbc7f994aa4 · outbound

This paper cites Dream- clear: High-capacity real-world image restoration with privacy-safe dataset curation.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Dream- clear: High-capacity real-world image restoration with privacy-safe dataset curation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.225231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1ac688d6-1ae7-4276-a1a3-fc2f7784cf53 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration On the Opportunities and Risks of Foundation Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:47.900675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6a6fdac-3f9d-4ded-a28a-c7a1dacd7653 · outbound

This paper cites Grids: Grouped multiple-degradation restoration with image degradation similarity.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Grids: Grouped multiple-degradation restoration with image degradation similarity

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.209168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9d75580b-00e3-4c5c-8c20-a687842d0556 · outbound

This paper cites Modeling the background for incremental learning in semantic segmentation.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Modeling the background for incremental learning in semantic segmentation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.192459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6baa1bb2-53a7-4939-805b-12ae303d15b1 · outbound

This paper cites Restoreagent: Autonomous image restoration agent via multimodal large language models.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Restoreagent: Autonomous image restoration agent via multimodal large language models

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.176603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 379469ad-1dd1-47b2-ab65-f98b7664205f · outbound

This paper cites Learn- ing a sparse transformer network for effective image derain- ing.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Learn- ing a sparse transformer network for effective image derain- ing

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.158387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2bec1463-9be1-47f2-923f-e4616d4714de · outbound

This paper cites A comparative study of image restoration networks for general backbone network design.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration A comparative study of image restoration networks for general backbone network design

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.142646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5f9dcb50-2d18-48fe-9edd-a75e064faac5 · outbound

This paper cites Instruc- tir: High-quality image restoration following human instruc- tions.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Instruc- tir: High-quality image restoration following human instruc- tions

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.126711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 35a9251a-2852-4069-97c6-291dac9753ff · outbound

This paper cites Multi-scale separable net- work for ultra-high-definition video deblurring.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Multi-scale separable net- work for ultra-high-definition video deblurring

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.109542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8373410d-9af2-47b7-bb84-6a0bb6f82f11 · outbound

This paper cites Dancing in the dark: A benchmark towards general low-light video enhancement.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Dancing in the dark: A benchmark towards general low-light video enhancement

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.091759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 81e29c59-5d92-44a8-8476-85deab0f9cae · outbound

This paper cites OneRestore: A Universal Restoration Framework for Composite Degradation.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration OneRestore: A Universal Restoration Framework for Composite Degradation

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-12T04:28:48.354081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7d43e651-9dd3-49aa-b8ff-902e4be08297 · outbound

This paper cites Denoising diffu- sion probabilistic models.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Denoising diffu- sion probabilistic models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:47.946660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39fd394c-4395-434e-92ef-0c2d4f2512a2 · outbound

This paper cites Single image super-resolution from transformed self-exemplars.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Single image super-resolution from transformed self-exemplars

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.062191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 72499f47-0f36-48e4-a953-791753074422 · outbound

This paper cites Multi-scale progressive fusion network for single image deraining.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Multi-scale progressive fusion network for single image deraining

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.046559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0b59cdb8-ff60-4495-821c-932953bfe8ef · outbound

This paper cites Autodir: Automatic all-in-one image restoration with latent diffusion.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Autodir: Automatic all-in-one image restoration with latent diffusion

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.030890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f92f55b0-6bc6-4b82-827a-ea5c286b6272 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Adam: A Method for Stochastic Optimization

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:47.965883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b56b6d01-cb0c-4b61-bb4d-0405fb59438f · outbound

This paper cites Segment any- thing.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Segment any- thing

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:47.971273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ab3859a-5b7f-4aab-81f4-8f55b2beb779 · outbound

This paper cites Efficient frequency domain-based trans- formers for high-quality image deblurring.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Efficient frequency domain-based trans- formers for high-quality image deblurring

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:49.001548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e54891a3-8205-4dcd-89dc-8a4c52d6c3aa · outbound

This paper cites Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:47.980714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99635392-5e4d-4df8-ac2b-48a6ee66dda8 · outbound

This paper cites Benchmarking single- image dehazing and beyond.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Benchmarking single- image dehazing and beyond

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.984547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2c4912f1-b593-43b2-907d-b1cc2bebf64b · outbound

This paper cites All-in-one image restoration for unknown cor- ruption.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration All-in-one image restoration for unknown cor- ruption

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.967552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c6ec0094-b296-4d88-9b71-de825bed0615 · outbound

This paper cites Embedding fourier for ultra-high-definition low-light image enhancement.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Embedding fourier for ultra-high-definition low-light image enhancement

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.948666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 25412ae7-dc5f-4bcf-85de-66178224f573 · outbound

This paper cites Toward Real-world Single Image Deraining: A New Benchmark and Beyond.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Toward Real-world Single Image Deraining: A New Benchmark and Beyond

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:47.999937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a07c874-cc8c-4812-97dc-ff0d7af3e985 · outbound

This paper cites Lsdir: A large scale dataset for image restoration.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Lsdir: A large scale dataset for image restoration

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.932029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c12a364b-45c6-49fc-bfdb-4e351462a5bf · outbound

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

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Swinir: Image restoration us- ing swin transformer

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:48.010330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62cc0347-369e-4a09-a253-09f7567ff350 · outbound

This paper cites Improving image restoration through removing degradations in textual repre- sentations.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Improving image restoration through removing degradations in textual repre- sentations

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.903355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e25d036f-678f-47fe-aa5b-7c88072b3566 · outbound

This paper cites Residual denoising diffu- sion models.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Residual denoising diffu- sion models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.887050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 38c116c6-7fb5-4719-81b3-0bfa586b26e7 · outbound

This paper cites Tape: Task-agnostic prior embedding for image restoration.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Tape: Task-agnostic prior embedding for image restoration

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.870549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ab63e1ab-e1da-441c-a58f-a6b318fe3878 · outbound

This paper cites Degae: A new pretraining paradigm for low-level vision.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Degae: A new pretraining paradigm for low-level vision

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.854720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d94503c7-26c2-4c50-a0fa-e76ee3cc5676 · outbound

This paper cites Image restoration with mean-reverting stochastic differential equations.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Image restoration with mean-reverting stochastic differential equations

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.839881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e87fbf1f-a01b-4179-8cbb-17c0da3936fd · outbound

This paper cites Controlling vision-language models for universal image restoration.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Controlling vision-language models for universal image restoration

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.825542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4afd7aa7-70ed-43f8-b8fc-3858f932f723 · outbound

This paper cites ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:48.045789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06f76bf2-b3cb-48d1-b66e-7b461fc9a742 · outbound

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

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration 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 2026-08-12T04:28:48.810371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fd011648-63c3-4ad3-911f-279d9d88ab67 · outbound

This paper cites Deep generalized unfolding networks for image restoration.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Deep generalized unfolding networks for image restoration

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.792889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 931a6222-6dd5-4290-9d58-6fd16ea4f7f9 · outbound

This paper cites Deep multi-scale convolutional neural network for dynamic scene deblurring.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Deep multi-scale convolutional neural network for dynamic scene deblurring

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.776668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4b39d216-48eb-4350-9c8a-12639c744ac8 · outbound

This paper cites Ntire 2019 challenge on video deblurring and super- resolution: Dataset and study.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Ntire 2019 challenge on video deblurring and super- resolution: Dataset and study

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.758155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5fbc12b5-59ef-4f37-a3b0-85f1dc9751cf · outbound

This paper cites Incremental few-shot ob- ject detection.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Incremental few-shot ob- ject detection

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.740502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 637f7d68-03fe-43ec-8eac-b28d5718c829 · outbound

This paper cites Promptir: Prompting for all-in- one image restoration.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Promptir: Prompting for all-in- one image restoration

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.723969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cb02902f-08d9-4bea-842d-7f0261af1a7a · outbound

This paper cites Attentive generative adversarial network for rain- drop removal from a single image.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Attentive generative adversarial network for rain- drop removal from a single image

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.707183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 66675bfb-0c09-476a-b24f-aee3f8645c61 · outbound

This paper cites Remov- ing raindrops and rain streaks in one go.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Remov- ing raindrops and rain streaks in one go

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.690658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 25c30351-2954-4480-9aae-4d25ff609036 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Learn- ing transferable visual models from natural language super- vision

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:48.090049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9725eca9-8d8c-4dd9-b5f6-04c85c42f328 · outbound

This paper cites Incremental learning of random forests for large- scale image classification.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Incremental learning of random forests for large- scale image classification

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.663649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation df7a9a9d-38b3-4830-8745-4fea05ecfd44 · outbound

This paper cites INTERN: A New Learning Paradigm Towards General Vision.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration INTERN: A New Learning Paradigm Towards General Vision

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:48.099034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9cb5975-a18c-4a13-bad1-2623440d70aa · outbound

This paper cites MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:48.103241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb0109bc-43f5-4c5d-a003-3448b6609485 · outbound

This paper cites Transweather: Transformer-based restoration of im- ages degraded by adverse weather conditions.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Transweather: Transformer-based restoration of im- ages degraded by adverse weather conditions

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:48.108726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28c316d3-37f9-4bdc-8515-c8e356bb55b6 · outbound

This paper cites Seeing dynamic scene in the dark: A high- quality video dataset with mechatronic alignment.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Seeing dynamic scene in the dark: A high- quality video dataset with mechatronic alignment

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.635843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 59ef3d99-212e-49f3-a011-68ad386b5d7f · outbound

This paper cites Zero-reference low-light enhancement via physical quadru- ple priors.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Zero-reference low-light enhancement via physical quadru- ple priors

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.619444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 08b16849-7471-4293-9600-504d5a8ed728 · outbound

This paper cites Real-esrgan: Training real-world blind super-resolution with pure synthetic data.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Real-esrgan: Training real-world blind super-resolution with pure synthetic data

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.603955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation daee624e-2a4e-4e76-9bd0-08afa6adec15 · outbound

This paper cites Deep retinex decomposition for low-light enhancement.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Deep retinex decomposition for low-light enhancement

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.588264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 13a2ce6b-4572-4c9d-9e45-750e5e793b88 · outbound

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

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Diffir: Efficient diffusion model for image restoration

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.572208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c53b71b0-0e51-4de1-8f26-f43229b2eb22 · outbound

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

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Real-world Noisy Image Denoising: A New Benchmark

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-12T04:28:48.139066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84a7e17d-307a-4572-b7ec-173e52878c65 · outbound

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

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Scaling up to excellence: Practicing model scaling for photo- realistic image restoration in the wild

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.555023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5ccfb797-8339-4251-beb1-e81e62f45bf4 · outbound

This paper cites Boosting continual learning of vision-language models via mixture-of-experts adapters.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Boosting continual learning of vision-language models via mixture-of-experts adapters

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.539288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 537e8811-dcc0-40fa-af38-54c4eb412c1e · outbound

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

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Restormer: Efficient transformer for high-resolution image restoration

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.523387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 67d581e7-b037-45e0-9106-a2fb92801302 · outbound

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

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Ingredient-oriented multi- degradation learning for image restoration

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.507522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 13b6499e-530e-49e9-b20f-d7d696ec7eb9 · outbound

This paper cites Mc- blur: A comprehensive benchmark for image deblurring.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Mc- blur: A comprehensive benchmark for image deblurring

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.490898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 03855269-7aa0-4ff5-b4a0-a0cb74073e99 · outbound

This paper cites Hazerd: an out- door scene dataset and benchmark for single image dehazing.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Hazerd: an out- door scene dataset and benchmark for single image dehazing

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.472313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3e841af3-f229-4b5e-a965-cbe8fb3e6093 · outbound

This paper cites Selective hourglass mapping for universal image restoration based on diffusion model.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Selective hourglass mapping for universal image restoration based on diffusion model

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.453893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e28523f9-9d16-413c-8908-5c61fee30bd1 · outbound

This paper cites Image de-raining via con- tinual learning.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Image de-raining via con- tinual learning

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.438002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c4b75d7c-12fe-4d78-89b6-c04c99de58b2 · outbound

This paper cites Led- net: Joint low-light enhancement and deblurring in the dark.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Led- net: Joint low-light enhancement and deblurring in the dark

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.421777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b4611f01-5e3f-4c06-a21b-6f5da65cb16b · outbound

This paper cites Wave-mamba: Wavelet state space model for ultra-high- 10 definition low-light image enhancement.

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration Wave-mamba: Wavelet state space model for ultra-high- 10 definition low-light image enhancement

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:28:48.405309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation f3c49130-4316-4ff8-8698-4b0b1e7ae7a2 · inbound

UniRestorer: Universal Image Restoration via Adaptively Estimating Image Degradation at Proper Granularity cites this paper.

UniRestorer: Universal Image Restoration via Adaptively Estimating Image Degradation at Proper Granularity FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-10T23:34:51.611655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f066de0e-071c-4b01-b12e-25dab29bada4 · inbound

DGSolver: Diffusion Generalist Solver with Universal Posterior Sampling for Image Restoration cites this paper.

DGSolver: Diffusion Generalist Solver with Universal Posterior Sampling for Image Restoration FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:27.858181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bac51ea-7fb4-4c39-86a7-580e923ee911 · inbound

Degradation-Aware Metric Prompting for Hyperspectral Image Restoration cites this paper.

Degradation-Aware Metric Prompting for Hyperspectral Image Restoration FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T14:30:59.944074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.