3 papers
cs.CV2026
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…
cs.CV2025
SOI is the Root of All Evil: Quantifying and Breaking Similar Object Interference in Single Object Tracking
Yipei Wang, Shiyu Hu, Shukun Jia +6
In this paper, we present the first systematic investigation and quantification of Similar Object Interference (SOI), a long-overlooked yet critical bottleneck in Single Object Tra…
cs.CV2024
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…