Research map / Architectures and efficiency / RNNs and normalization
On Human Motion Prediction Using Recurrent Neural Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace the recurrent prediction model with a zero-velocity predictor | Human 3.6M motion prediction · Human 3.6M Average, 400 ms | mean angle error: 1.20 -> 1.15 | Hurt |
| use sampling-based loss instead of feeding ground truth at each decoder step (ablation) | single-action model · Human 3.6M Walking, 400 ms | mean angle error: 1.34 -> 1.20 | Helped |
| add residual connections to model motion derivatives (ablation) | single-action model with sampling-based loss · Human 3.6M Walking, 400 ms | mean angle error: 1.20 -> 1.09 | Helped |
| train the residual model on multiple actions rather than one action (ablation) | Human 3.6M motion prediction · Human 3.6M Walking, 400 ms | mean angle error: 1.09 -> 0.81 | Helped |
| add action labels to the multi-action model (ablation) | residual multi-action model · Human 3.6M Walking, 400 ms | mean angle error: 0.78 -> 0.81 | Hurt |
| share encoder and decoder weights (ablation) | residual supervised multi-action model · Human 3.6M Walking, 400 ms | mean angle error: 0.91 -> 0.81 | Helped |
| use the zero-velocity predictor instead of SRNN | Human 3.6M motion prediction · Human 3.6M Walking, 400 ms | mean angle error: 1.30 -> 1.15 | Helped |
Closest papers by meaning
- A Neural Temporal Model for Human Motion Prediction (CVPR 2019 · similarity 0.90)
- Context-Aware Human Motion Prediction (CVPR 2020 · similarity 0.90)
- Deep Representation Learning for Human Motion Prediction and Classification (CVPR 2017 · similarity 0.90)
- HVIS: A Human-like Vision and Inference System for Human Motion Prediction (AAAI 2025 · similarity 0.87)
- Motion Diversification Networks (CVPR 2024 · similarity 0.86)
- SimpliHuMoN: Simplifying Human Motion Prediction (NeurIPS 2026 · similarity 0.86)
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