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3D Depth Estimation datasets

archive 2025-07-28

10 datasets carry the task tag "3D Depth Estimation" (the task itself: 3D Depth Estimation), ordered by the archive's paper count. Page 1 of 1: 10 shown of 10. 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

3D Depth Estimation datasets 1–10 of 10

HUMAN4D is a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by a professional marker-based MoCap, a volumetric capture and an audio recording system.
9 papers · 0 benchmarks
Are current 3D object tracking methods truely robust enough for low-fidelity depth sensors like the iPhone LiDAR?
8 papers · 2 benchmarks
DurLAR (A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery)
DurLAR is a high-fidelity 128-channel 3D LiDAR dataset with panoramic ambient (near infrared) and reflectivity imagery for multi-modal autonomous driving applications.
5 papers · 0 benchmarks
Relative Human (RH) contains multi-person in-the-wild RGB images with rich human annotations, including: Depth layers: relative depth relationship/ordering between all people in the image.
4 papers · 2 benchmarks
A real-world dataset, with hyper-accurate digital counterpart & comprehensive ground-truth annotation.
2 papers · 1 benchmark
DRACO20K dataset is used for evaluating object canonicalization on methods that estimate a canonical frame from a monocular input image.
2 papers · 0 benchmarks
Pano3D is a new benchmark for depth estimation from spherical panoramas.
2 papers · 0 benchmarks
WinSyn (WinSyn: A High Resolution Testbed for Synthetic Data)
75k photos of windows + 21k synthetic renders of building windows.
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.