Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency

Author:

Luo Zhipeng1,Cai Zhongang1,Zhou Changqing2,Zhang Gongjie3,Zhao Haiyu2,Yi Shuai2,Lu Shijian3,Li Hongsheng4,Zhang Shanghang5,Liu Ziwei1

Affiliation:

1. Nanyang Technological University,S-Lab

2. Sensetime Research

3. Nanyang Technological University

4. Chinese University of Hong Kong

5. UC Berkeley

Publisher

IEEE

Cited by 51 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. Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking With Transformer;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-09

2. Self-supervised domain adaptation on point clouds via homomorphic augmentation;Computers & Graphics;2024-06

3. WLST: Weak Labels Guided Self-training for Weakly-supervised Domain Adaptation on 3D Object Detection;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. BEVUDA: Multi-geometric Space Alignments for Domain Adaptive BEV 3D Object Detection;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

5. PLS: Unsupervised Domain Adaptation for 3d Object Detection Via Pseudo-Label Sizes;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

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