Search Results for author: Shengjing Tian

Found 4 papers, 0 papers with code

MirrorAttack: Backdoor Attack on 3D Point Cloud with a Distorting Mirror

no code implementations9 Mar 2024 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.

Backdoor Attack Specificity

Small Object Tracking in LiDAR Point Cloud: Learning the Target-awareness Prototype and Fine-grained Search Region

no code implementations24 Jan 2024 Shengjing Tian, Yinan Han, Xiuping Liu, Xiantong Zhao

To this end, we propose a Siamese network-based method for small object tracking in the LiDAR point cloud, which is composed of the target-awareness prototype mining (TAPM) module and the regional grid subdivision (RGS) module.

Object Tracking

OST: Efficient One-stream Network for 3D Single Object Tracking in Point Clouds

no code implementations16 Oct 2022 Xiantong Zhao, Yinan Han, Shengjing Tian, Jian Liu, Xiuping Liu

Although recent Siamese network-based trackers have achieved impressive perceptual accuracy for single object tracking in LiDAR point clouds, they advance with some heavy correlation operations on relation modeling and overlook the inherent merit of arbitrariness compared to multiple object tracking.

3D Single Object Tracking Multiple Object Tracking

Towards Class-agnostic Tracking Using Feature Decorrelation in Point Clouds

no code implementations28 Feb 2022 Shengjing Tian, Jun Liu, Xiuping Liu

In this work, we investigate a more challenging task in the LiDAR point clouds, class-agnostic tracking, where a general model is supposed to be learned for any specified targets of both observed and unseen categories.

Benchmarking Object Tracking

Cannot find the paper you are looking for? You can Submit a new open access paper.