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Image Restoration datasets
archive 2025-07-28
18 datasets carry the task tag "Image Restoration" (the task itself: Image Restoration), ordered by the archive's paper count. Page 1 of 1: 18 shown of 18. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
Image Restoration datasets 1–18 of 18
SIDD (Smartphone Image Denoising Dataset)
SIDD is an image denoising dataset containing 30,000 noisy images from 10 scenes under different lighting conditions using five representative smartphone cameras.
245 papers · 2 benchmarks
Color BSD68 dataset for image denoising benchmarks is part of The Berkeley Segmentation Dataset and Benchmark.
142 papers · 15 benchmarks
Raindrop is a set of image pairs, where each pair contains exactly the same background scene, yet one is degraded by raindrops and the other one is free from raindrops.
120 papers · 1 benchmark
Consists of 8,422 blurry and sharp image pairs with 65,784 densely annotated FG human bounding boxes.
95 papers · 4 benchmarks
PIRM (Perceptual Image Restoration and Manipulation)
The PIRM dataset consists of 200 images, which are divided into two equal sets for validation and testing.
32 papers · 1 benchmark
TinyPerson is a benchmark for tiny object detection in a long distance and with massive backgrounds.
25 papers · 0 benchmarks
DocUNet (Document Image Unwarping via a Stacked U-Net)
Various documents dataset.
23 papers · 3 benchmarks
CDD-11 (Composite Degradation Dataset 11)
An image restoration dataset
21 papers · 1 benchmark
A large-scale dataset of ~29.5K rain/rain-free image pairs that covers a wide range of natural rain scenes.
11 papers · 0 benchmarks
The first ultra-high-definition image demoireing dataset, consisting of 4,500 4K resolution training pairs and 500 standard 4K resolution validation pairs.
2 papers · 1 benchmark
The existing multi-modality image fusion dataset lacks comprehensive coverage of adverse weather scenarios.
1 paper · 0 benchmarks
Synthetic training set: This set is constructed in the following two steps and will be used for estimation/training purposes.
1 paper · 0 benchmarks
HAC (Hybrid Adverse Conditions)
HAC is a dataset for learning and benchmarking arbitrary Hybrid Adverse Conditions restoration.
1 paper · 0 benchmarks
HRI (High-resolution Rainy Image)
The HRI Dataset comprises a total of 3,200 image pairs.
1 paper · 0 benchmarks
The Sentinel-2 satellite carries 12 CMOS detectors for the VNIR bands, with adjacent detectors having overlapping fields of view that result in overlapping regions in level-1 B (L1B) images.
1 paper · 0 benchmarks
RawNIND (Raw Natural Image Noise Dataset)
The Raw Natural Image Noise Dataset (RawNIND) is a diverse collection of paired raw images designed to support the development of denoising models that generalize across sensors, image development workflows, and styles.
1 paper · 0 benchmarks
Smartphone cameras are ubiquitous in daily life, yet their performance can be severely impacted by dirty lenses, leading to degraded image quality.
1 paper · 0 benchmarks
Contains three difficult real-world scenarios: uncontrolled videos taken by UAVs and manned gliders, as well as controlled videos taken on the ground.
1 paper · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.