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Found 3 papers, 1 papers with code
Unveiling the Power of Self-supervision for Multi-view Multi-human Association and Tracking
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.
From a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera Calibration
We tackle a new problem of multi-view camera and subject registration in the bird's eye view (BEV) without pre-given camera calibration.
Self-supervised Social Relation Representation for Human Group Detection
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.
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