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Stereo Disparity Estimation datasets

archive 2025-07-28

7 datasets carry the task tag "Stereo Disparity Estimation" (the task itself: Stereo Disparity Estimation), ordered by the archive's paper count. Page 1 of 1: 7 shown of 7. 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

Stereo Disparity Estimation datasets 1–7 of 7

KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) is one of the most popular datasets for use in mobile robotics and autonomous driving.
3,661 papers · 137 benchmarks
The Middlebury 2014 dataset contains a set of 23 high resolution stereo pairs for which known camera calibration parameters and ground truth disparity maps obtained with a structured light scanner are available.
59 papers · 2 benchmarks
Spring (Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo)
Spring is a large, high-resolution and high-detail, computer-generated benchmark for scene flow, optical flow, and stereo.
29 papers · 3 benchmarks
SERV-CT (SERV-CT: A disparity dataset from CT for validation of endoscopic 3D reconstruction)
Endoscopic stereo reconstruction for surgical scenes gives rise to specific problems, including the lack of clear corner features, highly specular surface properties, and the presence of blood and smoke.
5 papers · 0 benchmarks
VBR (VBR: A Vision Benchmark in Rome)
This dataset presents a vision and perception research dataset collected in Rome, featuring RGB data, 3D point clouds, IMU, and GPS data.
3 papers · 0 benchmarks
GUISS dataset (Meshes, textures, Blend files, stereo datasets, depth maps, depth estimations))
We provide all the expected data inputs to GUISS such as meshes, texture images, and blend files.
1 paper · 0 benchmarks
L1BSR (L1BSR dataset)
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

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.