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About this paper
Longzhong Lin, Xuewu Lin, Tianwei Lin, Lichao Huang, Rong Xiong, Yue Wang
This paper from Zhejiang University and Horizon Robotics introduces Evolving and Distinct Anchors (EDA), a new paradigm for multimodal motion prediction that combines the benefits of prediction-based and anchor-based methods. EDA achieves state-of-the-art performance on the Waymo Open Motion Dataset by allowing prediction anchors to evolve adaptively and then ensuring their diversity through selection.
Key insights
- Allowing anchors to evolve based on intermediate network outputs enables them to adapt to specific scenes, improving regression accuracy.
- Applying Non-Maximum Suppression (NMS) to select distinct anchors mitigates prediction clustering and maintains diversity.
- The combination of evolving and distinct anchors effectively balances the trade-off between regression accuracy and prediction diversity in multimodal motion forecasting.
Summary by alphaXiv.
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