Bridging the Gap: Improving Domain Generalization in Trajectory Prediction

Author:

Wang Zhibo1ORCID,Guo Jiayu1,Zhang Haiqiang2ORCID,Wan Ru2,Zhang Junping3ORCID,Pu Jian1ORCID

Affiliation:

1. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China

2. Mogo Auto Intelligence and Telematics Information Technology Co., Ltd, Beijing, China

3. Shanghai Key Lab of Intelligent Information Processing and the School of Computer Science, Fudan University, Shanghai, China

Funder

Shanghai Municipal Science and Technology Major Project

Shanghai Center for Brain Science and Brain-Inspired Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Automotive Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Multi-Task Learning Network With a Collision-Aware Graph Transformer for Traffic-Agents Trajectory Prediction;IEEE Transactions on Intelligent Transportation Systems;2024-07

2. Robustness in trajectory prediction for autonomous vehicles: a survey;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

3. Predictive Time-Dependent Model Through the Conjunction of Bayes Theorem and Mitchell Criteria;2024 IEEE 4th International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB);2024-04-19

4. Leveraging Smooth Deformation Augmentation for LiDAR Point Cloud Semantic Segmentation;IEEE Transactions on Intelligent Vehicles;2024-02

5. Subclassified Loss: Rethinking Data Imbalance from Subclass Perspective for Semantic Segmentation;IEEE Transactions on Intelligent Vehicles;2023

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