IMR: Iterative Mode-World Weighted Regression for Multi-Agent Trajectory Prediction
Multi-agent motion prediction is essential for automated vehicles to understand the intentions of surrounding vehicles. However, previous prediction-based and anchor-based methods have limitations in mode diversity and prediction accuracy, respectively. These limitations may cause inadequate safety assessments and behavioral deviations in automated vehicles. To address this issue, a mode-world weighted regression loss is proposed to bridge the gap between these features. Specifically, this approach mitigates mode collapse while simultaneously improving world ranking and top-1 confidence. Furthermore, the proposed iterative decoder improves prediction accuracy by recurrently and segmentall...
| Authors | Honglin Wang, Shiyao Pan, Yun-Fu Liu |
|---|---|
| Primary category | cs.RO |
| Published | 6 July 2026 |
| Last updated at source | 6 July 2026 |
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