no code implementations • 31 Jan 2024 • Wei Feng, Feifan Wang, Ruize Han, Zekun Qian, Song Wang
Multi-view multi-human association and tracking (MvMHAT), is a new but important problem for multi-person scene video surveillance, aiming to track a group of people over time in each view, as well as to identify the same person across different views at the same time, which is different from previous MOT and multi-camera MOT tasks only considering the over-time human tracking.
1 code implementation • 19 Dec 2022 • Zekun Qian, Ruize Han, Wei Feng, Feifan Wang, Song Wang
We tackle a new problem of multi-view camera and subject registration in the bird's eye view (BEV) without pre-given camera calibration.
1 code implementation • 8 Mar 2022 • Jiacheng Li, Ruize Han, Haomin Yan, Zekun Qian, Wei Feng, Song Wang
The core of human group detection is the human social relation representation and division. In this paper, we propose a new two-stage multi-head framework for human group detection.