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Models/MSR-GCN

MSR-GCN

Reported on 6 benchmarks across 3 tasks · 1 paper · 3 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision2 results

Pose EstimationonHuman3.6M
Average MPJPE (mm) @ 1000 ms· 2021-08-16
114.2
best: 149.2 (Forecast LSTM)
SOTA
MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction arXiv:2108.07152
Pose EstimationonHuman3.6M
Average MPJPE (mm) @ 400ms· 2021-08-16
62.9
best: 80.8 (Forecast LSTM)
MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction arXiv:2108.07152

Methodology2 results

3DonHuman3.6M
Average MPJPE (mm) @ 1000 ms· 2021-08-16
114.2
best: 149.2 (Forecast LSTM)
SOTA
MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction arXiv:2108.07152
3DonHuman3.6M
Average MPJPE (mm) @ 400ms· 2021-08-16
62.9
best: 80.8 (Forecast LSTM)
MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction arXiv:2108.07152

Audio2 results

1 Image, 2*2 StitchionHuman3.6M
Average MPJPE (mm) @ 1000 ms· 2021-08-16
114.2
best: 149.2 (Forecast LSTM)
SOTA
MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction arXiv:2108.07152
1 Image, 2*2 StitchionHuman3.6M
Average MPJPE (mm) @ 400ms· 2021-08-16
62.9
best: 80.8 (Forecast LSTM)
MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction arXiv:2108.07152