3D Multi-Person Mesh Recovery

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.

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

2 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

12 shown of 12 papers with code (12 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.

• SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation
  29 Sep 2023 2 repositories listed
  1) For the data scaling, we perform a systematic investigation on 32 EHPS datasets, including a wide range of scenarios that a model trained on any single dataset cannot handle.
• Monocular, One-stage, Regression of Multiple 3D People
  27 Aug 2020 2 repositories listed
  Through a body-center-guided sampling process, the body mesh parameters of all people in the image are easily extracted from the Mesh Parameter map.
• AiOS: All-in-One-Stage Expressive Human Pose and Shape Estimation
  26 Mar 2024 1 repository listed
  Expressive human pose and shape estimation (a.
• Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery in a Single Shot
  22 Feb 2024 1 repository listed Syntology ran 8 of 9 samples · 1 unverified · 9 pointer-only (licence)
  We present Multi-HMR, a strong sigle-shot model for multi-person 3D human mesh recovery from a single RGB image.
• Instance-aware Contrastive Learning for Occluded Human Mesh Reconstruction
  1 Jan 2024 1 repository listed
  A simple yet effective method for occlusion-robust 3D human mesh reconstruction from a single image is presented in this paper.
• Reconstructing Groups of People with Hypergraph Relational Reasoning
  30 Aug 2023 1 repository listed
  To address the obstacles, we fully exploit crowd features for reconstructing groups of people from a monocular image.
• One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer
  28 Mar 2023 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  It is challenging to perform this task with a single network due to resolution issues, i.
• Body Size and Depth Disambiguation in Multi-Person Reconstruction from Single Images
  2 Nov 2021 1 repository listed
  We address the problem of multi-person 3D body pose and shape estimation from a single image.
• Collaborative Regression of Expressive Bodies using Moderation
  11 May 2021 1 repository listed
  Second, human shape is highly correlated with gender, but existing work ignores this.
• AGORA: Avatars in Geography Optimized for Regression Analysis
  29 Apr 2021 1 repository listed
  Additionally, we fine-tune methods on AGORA and show improved performance on both AGORA and 3DPW, confirming the realism of the dataset.
• Monocular Expressive Body Regression through Body-Driven Attention
  20 Aug 2020 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  To understand how people look, interact, or perform tasks, we need to quickly and accurately capture their 3D body, face, and hands together from an RGB image.
• Expressive Body Capture: 3D Hands, Face, and Body from a Single Image
  11 Apr 2019 1 repository listed
  We use the new method, SMPLify-X, to fit SMPL-X to both controlled images and images in the wild.

Syntology lines on 3 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.