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SotA/Methodology/3D/Human3.6M

3D on Human3.6M

Metric: Average MPJPE (mm) @ 400ms (higher is better)

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#Model↕Average MPJPE (mm) @ 400ms▼AugmentationsPaperDate↕Code
1Forecast LSTM80.8No--Code
2AnyPose180.6NoAnyPose: Anytime 3D Human Pose Forecasting via N...2023-09-09-
3STS-GCN65.8NoSpace-Time-Separable Graph Convolutional Network...2021-10-09Code
4LTD-GCN63.5NoLearning Trajectory Dependencies for Human Motio...2019-08-15Code
5MSR-GCN62.9NoMSR-GCN: Multi-Scale Residual Graph Convolution ...2021-08-16Code
6UNIMASK-M61.6NoA Unified Masked Autoencoder with Patchified Ske...2023-08-14-
7MotionMixer59.3NoMotionMixer: MLP-based 3D Human Body Pose Foreca...2022-07-01Code
8PGBIG58.5NoProgressively Generating Better Initial Guesses ...2022-03-30Code
9siMLPe57.3NoBack to MLP: A Simple Baseline for Human Motion ...2022-07-04Code
10GraphMixer56.7NoGraph-Guided MLP-Mixer for Skeleton-Based Human ...2023-04-07-
11ResChunk56.41NoMultiscale Residual Learning of Graph Convolutio...2023-08-31Code
12Sun et al.55.5NoTowards Accurate Human Motion Prediction via Ite...2023-05-08-
13EqMotion55NoEqMotion: Equivariant Multi-agent Motion Predict...2023-03-20Code
14AuxFormer54.1NoAuxiliary Tasks Benefit 3D Skeleton-based Human ...2023-08-17Code
15FMS-AM34.8NoRemembering What Is Important: A Factorised Mult...2023-05-19-
16MGCN34.4NoMulti-Graph Convolution Network for Pose Forecas...2023-04-11-
17GCNext30.5NoGCNext: Towards the Unity of Graph Convolutions ...2023-12-19Code