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Deblurring datasets
archive 2025-07-28
17 datasets carry the task tag "Deblurring" (the task itself: Deblurring), ordered by the archive's paper count. Page 1 of 1: 17 shown of 17. 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
Deblurring datasets 1–17 of 17
The GoPro dataset for deblurring consists of 3,214 blurred images with the size of 1,280×720 that are divided into 2,103 training images and 1,111 test images.
390 papers · 4 benchmarks
The dataset consists of 4,738 pairs of images of 232 different scenes including reference pairs.
100 papers · 6 benchmarks
Consists of 8,422 blurry and sharp image pairs with 65,784 densely annotated FG human bounding boxes.
95 papers · 4 benchmarks
This dataset focus on two blur types: camera motion blur and defocus blur.
34 papers · 0 benchmarks
The Dialog State Tracking Challenges 2 & 3 (DSTC2&3) were research challenge focused on improving the state of the art in tracking the state of spoken dialog systems.
33 papers · 5 benchmarks
The RSBlur dataset provides pairs of real and synthetic blurred images with ground truth sharp images.
18 papers · 2 benchmarks
REDS (REalistic and Diverse Scenes dataset
realistic and dynamic scenes)
The realistic and dynamic scenes (REDS) dataset was proposed in the NTIRE19 Challenge.
15 papers · 1 benchmark
QMUL-SurvFace is a surveillance face recognition benchmark that contains 463,507 face images of 15,573 distinct identities captured in real-world uncooperative surveillance scenes over wide space and time.
10 papers · 1 benchmark
This is a gun detection dataset with 51K annotated gun images for gun detection and other 51K cropped gun chip images for gun classification collected from a few different sources.
9 papers · 6 benchmarks
MSU BASED (MSU BASED Video Deblurring Dataset and Benchmark)
Qualitative dataset with real blurred videos, created by using beam-splitter setup in lab environment
7 papers · 1 benchmark
A dataset of over 65,000 pairs of incorrectly white-balanced images and their corresponding correctly white-balanced images.
7 papers · 0 benchmarks
Using the proposed beam-splitter acquisition system, we have collected a new real-world video deblurring dataset (BSD).
5 papers · 1 benchmark
A large-scale multi-scene dataset for stereo deblurring, containing 20,637 blurry-sharp stereo image pairs from 135 diverse sequences and their corresponding bidirectional disparities.
2 papers · 0 benchmarks
This dataset consists of blurred, noisy and defocused images.
2 papers · 0 benchmarks
DAVIDE ('Depth-Aware VIdeo DEblurring')
The DAVIDE dataset consists of synchronized blurred, depth, and sharp videos.
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
YorkTag provides pairs of sharp/blurred images containing fiducial markers and is proposed to train and qualitatively and quantitatively evaluate our model.
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.