Papers › Adaptive Multi-view and Temporal Fusing Transformer for 3D Human Pose Estimation
Adaptive Multi-view and Temporal Fusing Transformer for 3D Human Pose Estimation
Hui Shuai, Lele Wu, Qingshan Liu
This paper proposes a unified framework dubbed Multi-view and Temporal Fusing Transformer (MTF-Transformer) to adaptively handle varying view numbers and video length without camera calibration in 3D Human Pose Estimation (HPE). It consists of Feature Extractor, Multi-view Fusing Transformer (MFT), and Temporal Fusing Transformer (TFT). Feature Extractor estimates 2D pose from each image and fuses the prediction according to the confidence. It provides pose-focused feature embedding and makes subsequent modules computationally lightweight. MFT fuses the features of a varying number of views with a novel Relative-Attention block. It adaptively measures the implicit relative relationship between each pair of views and reconstructs more informative features. TFT aggregates the features of the whole sequence and predicts 3D pose via a transformer. It adaptively deals with the video of arbitrary length and fully unitizes the temporal information. The migration of transformers enables our model to learn spatial geometry better and preserve robustness for varying application scenarios. We report quantitative and qualitative results on the Human3.6M, TotalCapture, and KTH Multiview Football II. Compared with state-of-the-art methods with camera parameters, MTF-Transformer obtains competitive results and generalizes well to dynamic capture with an arbitrary number of unseen views.
In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.
Code
No code repository is listed for this paper in the archive or in Syntology's graph.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=7) | Average MPJPE (mm) | 28.5 | #4 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=7) | Multi-View or Monocular | Multi-View | #4 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=7) | Using 2D ground-truth joints | No | #4 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=1) | Average MPJPE (mm) | 29.4 | #6 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=1) | Multi-View or Monocular | Multi-View | #6 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=1) | Using 2D ground-truth joints | No | #6 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=7, N=1) | Average MPJPE (mm) | 49.4 | #59 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=7, N=1) | Multi-View or Monocular | Monocular | #59 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=7, N=1) | Using 2D ground-truth joints | No | #59 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=1, N=1) | Average MPJPE (mm) | 50.7 | #68 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=1, N=1) | Multi-View or Monocular | Monocular | #68 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Human3.6M | MTF-Transformer (M=0.4, T=1, N=1) | Using 2D ground-truth joints | No | #68 of 88 | Archive leaderboard | report |
| 3D Human Pose Estimation | Total Capture | MTF-Transformer (M=0.4, T=7) | Average MPJPE (mm) | 29.2 | #7 of 14 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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