DeconfuseTrack:Dealing with Confusion for Multi-Object Tracking

no code implementations • 5 Mar 2024 • Cheng Huang, Shoudong Han, Mengyu He, Wenbo Zheng, Yuhao Wei

Moreover, DeconfuseTrack achieves state-of-the-art performance on the MOT17 and MOT20 test sets, significantly outperforms the baseline tracker ByteTrack in metrics such as HOTA, IDF1, AssA.

Multi-Object Tracking Object

DeconfuseTrack: Dealing with Confusion for Multi-Object Tracking

no code implementations • CVPR 2024 • Cheng Huang, Shoudong Han, Mengyu He, Wenbo Zheng, Yuhao Wei

Moreover DeconfuseTrack achieves state-of-the-art performance on the MOT17 and MOT20 test sets significantly outperforms the baseline tracker ByteTrack in metrics such as HOTA IDF1 AssA.

Multi-Object Tracking Object

High-Resolution Boundary Detection for Medical Image Segmentation with Piece-Wise Two-Sample T-Test Augmented Loss

no code implementations • 4 Nov 2022 • Yucong Lin, Jinhua Su, Yuhang Li, Yuhao Wei, Hanchao Yan, Saining Zhang, Jiaan Luo, Danni Ai, Hong Song, Jingfan Fan, Tianyu Fu, Deqiang Xiao, Feifei Wang, Jue Hou, Jian Yang

Deep learning methods have contributed substantially to the rapid advancement of medical image segmentation, the quality of which relies on the suitable design of loss functions.

Boundary Detection Image Segmentation +3