Search Results for author: Fangzhen Li

Found 2 papers, 1 papers with code

ProIn: Learning to Predict Trajectory Based on Progressive Interactions for Autonomous Driving

no code implementations25 Mar 2024 Yinke Dong, Haifeng Yuan, Hongkun Liu, Wei Jing, Fangzhen Li, Hongmin Liu, Bin Fan

In this work, a progressive interaction network is proposed to enable the agent's feature to progressively focus on relevant maps, in order to better learn agents' feature representation capturing the relevant map constraints.

Autonomous Driving motion prediction

FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving

1 code implementation2 Aug 2023 Tengju Ye, Wei Jing, Chunyong Hu, Shikun Huang, Lingping Gao, Fangzhen Li, Jingke Wang, Ke Guo, Wencong Xiao, Weibo Mao, Hang Zheng, Kun Li, Junbo Chen, Kaicheng Yu

Building a multi-modality multi-task neural network toward accurate and robust performance is a de-facto standard in perception task of autonomous driving.

Autonomous Driving

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