The proposed model aims to alleviate the deleterious tasks competition, meanwhile improve the cooperation between detection and ReID.

Convolutional Neural Network (CNN) based object detec- tion and re-identification (ReID) have demonstrated excellent performance in multi-object tracking in the ...

A novel dual-path transformation network (DTN) is proposed that decouples the shared features into detection-specific and ReID-specific representations.

Oct 3, 2024 · The tracking problem involves finding correlations between successive frames of the same object, and current supervised MOT methods require a ...

Due to balanced accuracy and speed, joint learning detection and ReID-based one-shot models have drawn great attention in multi-object tracking(MOT).

Dec 15, 2020 · CSTrack proposes a strong ReID based one-shot MOT framework. It includes a novel cross-correlation network that can effectively impel the separate branches.

Oct 23, 2020 · Our analysis reveals that the competition of them inevitably hurts the learning of task-dependent representations, which further impedes the ...

51.4. Rethinking the competition between detection and ReID in Multi-Object Tracking. 2020. 2. SGT. 47.2, 53.7. Detection Recovery in Online Multi-Object ...

Article "Rethinking the competition between detection and ReID in Multi-Object Tracking" Detailed information of the J-GLOBAL is an information service ...

Sep 10, 2024 · Joint detection and tracking, or end-to-end tracking, aims to eliminate ReID feature matching by proposing a data-driven association of motion ...