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3D Shape Reconstruction datasets

archive 2025-07-28

9 datasets carry the task tag "3D Shape Reconstruction" (the task itself: 3D Shape Reconstruction), ordered by the archive's paper count. Page 1 of 1: 9 shown of 9. 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 Shape Reconstruction datasets 1–9 of 9

The Pix3D dataset is a large-scale benchmark of diverse image-shape pairs with pixel-level 2D-3D alignment.
142 papers · 5 benchmarks
For many fundamental scene understanding tasks, it is difficult or impossible to obtain per-pixel ground truth labels from real images.
108 papers · 4 benchmarks
ApolloCar3DT is a dataset that contains 5,277 driving images and over 60K car instances, where each car is fitted with an industry-grade 3D CAD model with absolute model size and semantically labelled keypoints.
17 papers · 14 benchmarks
4DFAB is a large scale database of dynamic high-resolution 3D faces which consists of recordings of 180 subjects captured in four different sessions spanning over a five-year period (2012 - 2017), resulting in a total of over 1,800,000 3D…
14 papers · 0 benchmarks
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
FewSOL (A Dataset for Few-Shot Object Learning in Robotic Environments)
The Few-Shot Object Learning (FewSOL) dataset can be used for object recognition with a few images per object.
4 papers · 0 benchmarks
A dataset of high resolution, textured scans of articulated left feet, useful for 3D shape representation learning.
4 papers · 0 benchmarks
The dataset is designed specifically to solve a range of computer vision problems (2D-3D tracking, posture) faced by biologists while designing behavior studies with animals.
3 papers · 0 benchmarks
Large Shape and Texture dataset (LAS&T) is a giant dataset of shapes and textures for tasks of visual shapes and textures identification and retrieval from single image.
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.