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Surface Normals Estimation datasets
archive 2025-07-28
12 datasets carry the task tag "Surface Normals Estimation" (the task itself: Surface Normals Estimation), ordered by the archive's paper count. Page 1 of 1: 12 shown of 12. 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
Surface Normals Estimation datasets 1–12 of 12
ScanNet is an instance-level indoor RGB-D dataset that includes both 2D and 3D data.
1,595 papers · 21 benchmarks
The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect.
986 papers · 16 benchmarks
The PASCAL Context dataset is an extension of the PASCAL VOC 2010 detection challenge, and it contains pixel-wise labels for all training images.
323 papers · 6 benchmarks
Taskonomy provides a large and high-quality dataset of varied indoor scenes.
147 papers · 2 benchmarks
IBims-1 (Independent benchmark images and matched scans v1)
iBims-1 (independent Benchmark images and matched scans - version 1) is a new high-quality RGB-D dataset, especially designed for testing single-image depth estimation (SIDE) methods.
34 papers · 2 benchmarks
GRIT (General Robust Image Task Benchmark)
The General Robust Image Task (GRIT) Benchmark is an evaluation-only benchmark for evaluating the performance and robustness of vision systems across multiple image prediction tasks, concepts, and data sources.
16 papers · 5 benchmarks
We introduce Stanford-ORB, a new real-world 3D Object inverse Rendering Benchmark.
16 papers · 3 benchmarks
Provides a large-scale synthetic dataset which contains accurate ground truth depth of various photo-realistic scenes.
4 papers · 0 benchmarks
Pano3D is a new benchmark for depth estimation from spherical panoramas.
2 papers · 0 benchmarks
SuperCaustics is a simulation tool made in Unreal Engine for generating massive computer vision datasets that include transparent objects.
2 papers · 0 benchmarks
50K synthetic renders of the human foot, with surface normals, masks and keypoints.
1 paper · 0 benchmarks
The dataset contains procedurally generated images of transparent vessels containing liquid and objects .
1 paper · 1 benchmark
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.