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Social GAN: Socially Acceptable Trajectories With Generative Adversarial Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Train with variety loss and use multiple sampled trajectories rather than a single sample (ablation) | SGAN · ETH, HOTEL, UNIV, ZARA1, ZARA2 (AVG) | ADE: 0.49 / 0.74 -> 0.39 / 0.58 | Helped |
| Draw more test samples without training with variety loss (ablation) | SGAN · ETH, HOTEL, UNIV, ZARA1, ZARA2 (AVG) | ADE: 0.49 / 0.74 -> 0.45 / 0.67 | No clear effect |
| Use the proposed pooling module (ablation) | SGAN-20V-20 · ETH, HOTEL, UNIV, ZARA1, ZARA2 (AVG) | ADE: 0.39 / 0.58 -> 0.41 / 0.61 | Hurt |
| Use the proposed pooling module (ablation) | SGAN · Synthetic collision-avoidance scenarios | socially acceptable collision avoidance | Helped |
| Train and evaluate with multiple samples but without variety loss (ablation) | SGAN · ETH and UCY datasets | ADE | No clear effect |
| Increase the variety-loss sample count to k=100 (ablation) | SGAN · ETH and UCY datasets | prediction accuracy: 33% | Helped |
| Pool context once rather than at every decoder time step (ablation) | SGAN-P · ETH and UCY datasets | speed: 16x | Helped |
Closest papers by meaning
- Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks (NeurIPS 2019 · similarity 0.92)
- SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints (CVPR 2019 · similarity 0.91)
- Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction (CVPR 2020 · similarity 0.88)
- Social-Transmotion: Promptable Human Trajectory Prediction (ICLR 2024 · similarity 0.88)
- FutureHuman3D: Forecasting Complex Long-Term 3D Human Behavior from Video Observations (CVPR 2024 · similarity 0.86)
- SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents (AAAI 2024 · similarity 0.85)
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