DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds

Author:

Ma Tao1,Yang Xuemeng2,Zhou Hongbin2,Li Xin3,Shi Botian2,Liu Junjie4,Yang Yuchen5,Liu Zhizheng6,He Liang3,Qiao Yu2,Li Yikang2,Li Hongsheng1

Affiliation:

1. The Chinese University of Hong Kong,Multimedia Laboratory

2. Shanghai Artificial Intelligence Laboratory

3. East China Normal University

4. South China University of Technology

5. Fudan University

6. ETH Zurich

Funder

Innovation and Technology Commission

Science and Technology Commission of Shanghai Municipality

Publisher

IEEE

Cited by 8 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. Advances in 3D pre-training and downstream tasks: a survey;Vicinagearth;2024-07-23

2. Rethinking Masked-Autoencoder-Based 3D Point Cloud Pretraining;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

3. Offline Tracking with Object Permanence;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

4. VeloVox: A Low-Cost and Accurate 4D Object Detector with Single-Frame Point Cloud of Livox LiDAR;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

5. SOAP: Cross-sensor Domain Adaptation for 3D Object Detection Using Stationary Object Aggregation Pseudo-labelling;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

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