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Fangze Lin

2 accepted papers

2025

JAM: Keypoint-Guided Joint Prediction after Classification-Aware Marginal Proposal for Multi-Agent Interaction

IROS 2025

Predicting the future motion of road participants is a critical task in autonomous driving. In this work, we address the challenge of low-quality generation of low-probability modes in multi-agent joint prediction. To tackle this issue, we propose a two-stage multi-agent interactive prediction frame

Cited by 0SourcecodeScholar
2024

PP-TIL: Personalized Planning for Autonomous Driving with Instance-based Transfer Imitation Learning

IROS 2024poster

Personalized motion planning holds significant importance within urban automated driving, catering to the unique requirements of individual users. Nevertheless, prior endeavors have frequently encountered difficulties in simultaneously addressing two crucial aspects: personalized planning within int…

Cited by 0SourcecodeScholar