Browse State-of-the-Art › 3D Depth Estimation
3D Depth Estimation
12 papers with code · 1 benchmark · 10 datasets archive 2025-07-28
Image: monodepth2
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| Relative Human (3 rows) | BEV | Putting People in their Place: Monocular Regression of 3D People in Depth | code | Syntology ran 3 of 8 samples · 5 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
10 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
1 subtask in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
12 shown of 12 papers with code (19 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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15 Dec 2021 4 repositories listed Syntology ran 3 of 8 samples · 5 unverified · 3 pointer-only (licence)To do so, we exploit a 3D body model space that lets BEV infer shapes from infants to adults.
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26 Jul 2019 4 repositories listed Syntology ran 1 of 7 samples · 6 unverifiedAlthough significant improvement has been achieved recently in 3D human pose estimation, most of the previous methods only treat a single-person case.
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14 Jun 2019 3 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)We tackle the fundamentally ill-posed problem of 3D human localization from monocular RGB images.
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27 Aug 2020 2 repositories listedThrough a body-center-guided sampling process, the body mesh parameters of all people in the image are easily extracted from the Mesh Parameter map.
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17 Sep 2019 2 repositories listedThis has led to the utilization of view synthesis as an indirect objective for learning depth estimation using efficient data acquisition procedures.
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29 May 2023 1 repository listedAdditionally, we propose a novel metric to measure task complexity of the framework which accounts for the visual parameters and the distribution of the spatial data.
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26 Aug 2020 1 repository listedRecovering multi-person 3D poses with absolute scales from a single RGB image is a challenging problem due to the inherent depth and scale ambiguity from a single view.
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15 Jun 2020 1 repository listedOur goal is to train a single network that learns to avoid these problems and generate a coherent 3D reconstruction of all the humans in the scene.
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7 Apr 2020 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 1 pointer-only (licence)Reliable and accurate 3D object detection is a necessity for safe autonomous driving.
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27 Apr 2019 1 repository listedTo provide users with an intuitive way to navigate the layout design space, we present a technique to systematically visualize a graph in diverse layouts using deep generative models.
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3 Apr 2019 1 repository listedSingle-view depth estimation suffers from the problem that a network trained on images from one camera does not generalize to images taken with a different camera model.
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15 Mar 2017 1 repository listedThese components are typically estimated using methods based on local correlation tracking.
Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections