4 papers
COAL: Counterfactual and Observation-Enhanced Alignment Learning for Discriminative Referring Multi-Object Tracking
Shukun Jia, Shiyu Hu, Yipei Wang +3
Referring Multi-Object Tracking (RMOT) faces a fundamental structural contradiction between the high-discriminability demand and the sparse semantic supervision. This mismatch is p…
FocusTrack: One-Stage Focus-and-Suppress Framework for 3D Point Cloud Object Tracking
Sifan Zhou, Jiahao Nie, Ziyu Zhao +2
In 3D point cloud object tracking, the motion-centric methods have emerged as a promising avenue due to its superior performance in modeling inter-frame motion. However, existing t…
Tracking by Detection and Query: An Efficient End-to-End Framework for Multi-Object Tracking
Shukun Jia, Shiyu Hu, Yichao Cao +3
Multi-object tracking (MOT) is primarily dominated by two paradigms: tracking-by-detection (TBD) and tracking-by-query (TBQ). While TBD offers modular efficiency, its fragmented as…
MAMCA -- Optimal on Accuracy and Efficiency for Automatic Modulation Classification with Extended Signal Length
Yezhuo Zhang, Zinan Zhou, Yichao Cao +2
With the rapid growth of the Internet of Things ecosystem, Automatic Modulation Classification (AMC) has become increasingly paramount. However, extended signal lengths offer a bou…