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Research map / Probabilistic and scientific modeling / Molecules and proteins

Interpretable Social Anchors for Human Trajectory Forecasting in Crowds

CVPR 2021 · Probabilistic and scientific modeling › Molecules and proteins · approach: Multimodal trajectory prediction · 54 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use interpretable social anchors with learned scene residualsSAnchor · TrajNet++ syntheticADE / FDE: 0.25/0.50 -> 0.22/0.45Helped
Use interpretable social anchors with learned scene residualsSAnchor · TrajNet++ syntheticCol-I: 1.2 -> 0.4Helped
Use interpretable social anchors with learned scene residualsSAnchor · TrajNet++ realADE / FDE: 0.57/1.24 -> 0.62/1.32Hurt
Use interpretable social anchors with learned scene residualsSAnchor · TrajNet++ realCol-I: 5.5 -> 4.2Helped
Add direction normalization to NN-LSTM (ablation)NN-LSTM · TrajNet++ syntheticADE / FDE: 0.25/0.50 -> 0.20/0.43Helped
Add direction normalization to NN-LSTM (ablation)NN-LSTM · TrajNet++ realADE / FDE: 0.58/1.24 -> 0.63/1.36Hurt
Add direction normalization to NN-LSTM (ablation)NN-LSTM · TrajNet++ realCol-I: 7.5 (0.25) -> 5.9Helped
Add direction normalization to WTA (ablation)WTA · TrajNet++ syntheticADE / FDE: 0.28/0.54 -> 0.22/0.45Helped
Add direction normalization to WTA (ablation)WTA · TrajNet++ realCol-I: 5.1 -> 4.4Helped
Add direction normalization to WTA (ablation)WTA · TrajNet++ realTop-3 ADE / FDE: 0.49/1.05 -> 0.54/1.15Hurt
Add direction normalization to SGAN (ablation)SGAN · TrajNet++ realCol-I: 5.9 -> 4.0Helped
Add direction normalization to CVAE (ablation)CVAE · TrajNet++ realADE / FDE: 0.60/1.28 -> 0.62/1.34Hurt

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