Browse State-of-the-Art › 3D Human Shape Estimation
3D Human Shape Estimation
19 papers with code · 2 benchmarks · 7 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
2 leaderboard tables shown for this task, 2 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 |
|---|---|---|---|---|---|
| SSP-3D (11 rows) | Hierarchical Probabilistic Humans | Hierarchical Kinematic Probability Distributions for 3D Human... | code | Syntology ran 6 of 11 samples · 5 unverified | Compare |
| MoVi (1 row) | STRAPS | Synthetic Training for Accurate 3D Human Pose and Shape Estimation... | code | Syntology ran 2 of 9 samples · 7 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
7 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
19 shown of 19 papers with code (33 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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18 Dec 2017 10 repositories listedThe main objective is to minimize the reprojection loss of keypoints, which allow our model to be trained using images in-the-wild that only have ground truth 2D annotations.
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1 Apr 2020 3 repositories listedAlthough current approaches have demonstrated the potential in real world settings, they still fail to produce reconstructions with the level of detail often present in the input images.
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7 Sep 2023 2 repositories listedWe present a novel human body model formulated by an extensive set of anthropocentric measurements, which is capable of generating a wide range of human body shapes and poses.
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16 Dec 2021 2 repositories listedFirst, ICON infers detailed clothed-human normals (front/back) conditioned on the SMPL(-X) normals.
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13 Mar 2025 1 repository listedWe propose Equivariant Tightness Fitting for Clothed Humans, or ETCH, a novel pipeline that estimates cloth-to-body surface mapping through locally approximate SE(3) equivariance, encoding tightness as displacement…
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23 Aug 2022 1 repository listedThe approach overcomes limitations of existing approaches that reconstruct 3D human shape from a single image, which require high-resolution images together with auxiliary data such as surface normal or a parametric…
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14 Jun 2022 1 repository listedSince paired data with images and 3D body shape are rare, we exploit two sources of information: (1) we collect internet images of diverse "fashion" models together with a small set of anthropometric measurements; (2)…
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29 Nov 2021 1 repository listed Syntology ran 3 of 11 samples · 8 unverifiedIn this work, we propose a method capable of capturing the dynamic 3D human shape from a monocular video featuring challenging body poses, without any additional input.
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24 Nov 2021 1 repository listedWe propose a pose analysis module that uses graph transformers to exploit structured and implicit joint correlations, and a mesh regression module that combines the extracted pose feature with the mesh template to…
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2 Nov 2021 1 repository listedWe address the problem of multi-person 3D body pose and shape estimation from a single image.
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18 Oct 2021 1 repository listedIn fact, we show that simply fine-tuning the batch normalization layers of the model is enough to achieve large gains.
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3 Oct 2021 1 repository listed Syntology ran 6 of 11 samples · 5 unverifiedThus, it is desirable to estimate a distribution over 3D body shape and pose conditioned on the input image instead of a single 3D reconstruction.
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1 Aug 2021 1 repository listed Syntology ran 2 of 9 samples · 7 unverifiedThe lack of diverse and accurate pose and shape training data becomes a major bottleneck, especially for scenes with occlusions in the wild.
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6 May 2021 1 repository listed Syntology ran 1 of 7 samples · 6 unverifiedIn this work, we present a single-stage model, Body Meshes as Points (BMP), to simplify the pipeline and lift both efficiency and performance.
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29 Apr 2021 1 repository listedAdditionally, we fine-tune methods on AGORA and show improved performance on both AGORA and 3DPW, confirming the realism of the dataset.
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21 Sep 2020 1 repository listed Syntology ran 2 of 9 samples · 7 unverifiedThus, we propose STRAPS (Synthetic Training for Real Accurate Pose and Shape), a system that utilises proxy representations, such as silhouettes and 2D joints, as inputs to a shape and pose regression neural network,…
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28 Jul 2020 1 repository listedWe present the first approach to volumetric performance capture and novel-view rendering at real-time speed from monocular video, eliminating the need for expensive multi-view systems or cumbersome pre-acquisition of a…
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2 Apr 2020 1 repository listedWe describe a physics-based method that simulates human bodies at rest in a bed with a pressure sensing mat, and present PressurePose, a synthetic dataset with 206K pressure images with 3D human poses and shapes.
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27 Sep 2019 1 repository listedOur approach is self-improving by nature, since better network estimates can lead the optimization to better solutions, while more accurate optimization fits provide better supervision for the network.
Syntology lines on 5 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