Single Object Tracking
Single object tracking (SOT) aims to accurately locate a specific object within a video sequence across multiple frames. Current research emphasizes improving robustness and efficiency, focusing on transformer-based architectures, Siamese networks, and multi-modal approaches that integrate data from RGB cameras, event cameras, LiDAR, and thermal sensors. These advancements are crucial for applications in autonomous driving, robotics, augmented reality, and video surveillance, driving progress in both algorithmic design and benchmark dataset development.
Papers
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NeighborTrack: Improving Single Object Tracking by Bipartite Matching with Neighbor Tracklets
Yu-Hsi Chen, Chien-Yao Wang, Cheng-Yun Yang, Hung-Shuo Chang, Youn-Long Lin, Yung-Yu Chuang, Hong-Yuan Mark Liao
CXTrack: Improving 3D Point Cloud Tracking with Contextual Information
Tian-Xing Xu, Yuan-Chen Guo, Yu-Kun Lai, Song-Hai Zhang
October 2, 2022
September 28, 2022
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August 4, 2022