5 papers
MambaTrack3D: A State Space Model Framework for LiDAR-Based Object Tracking under High Temporal Variation
Shengjing Tian, Yinan Han, Xiantong Zhao +2
Dynamic outdoor environments with high temporal variation (HTV) pose significant challenges for 3D single object tracking in LiDAR point clouds. Existing memory-based trackers ofte…
Adversarial Attacks on LiDAR-Based Tracking Across Road Users: Robustness Evaluation and Target-Aware Black-Box Method
Shengjing Tian, Xiantong Zhao, Yuhao Bian +2
In this study, we delve into the robustness of neural network-based LiDAR point cloud tracking models under adversarial attacks, a critical aspect often overlooked in favor of perf…
Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions
Xiantong Zhao, Xiuping Liu, Shengjing Tian +1
3D single object tracking (3DSOT) in LiDAR point clouds is a critical task for outdoor perception, enabling real-time perception of object location, orientation, and motion. Despit…
iBA: Backdoor Attack on 3D Point Cloud via Reconstructing Itself
Yuhao Bian, Shengjing Tian, Xiuping Liu
The widespread deployment of Deep Neural Networks (DNNs) for 3D point cloud processing starkly contrasts with their susceptibility to security breaches, notably backdoor attacks. T…
OST: Efficient One-stream Network for 3D Single Object Tracking in Point Clouds
Xiantong Zhao, Yinan Han, Shengjing Tian +2
Although recent Siamese network-based trackers have achieved impressive perceptual accuracy for single object tracking in LiDAR point clouds, they usually utilized heavy correlatio…