3 accepted papers
Referring Multi-Object Tracking (RMOT) aims to detect and track specific objects based on natural language expressions. Previous methods typically rely on sentence-level vision-language alignment, often failing to exploit fine-grained linguistic cues that are crucial for distinguishing objects with…
Multi-object tracking (MOT) has gained remarkable progress in recent years, while due to the complexity of real-world environments, there are still many challenges that remain unsolved, such as object occlusion and deformation. To effectively alleviate this problem, we propose a simple yet effective…
Referring multi-object tracking is a new rising research topic that aims at detecting and tracking the referred objects in a video sequence based on a natural language expression. Compared with traditional multi-object tracking, this setting guides object tracking with high-level semantic informatio…