We present a novel transformer-based architecture for global multi-object tracking. Our network takes a short sequence of frames as input and produces global trajectories for all objects. The core component is a global tracking transformer that operates on objects from all frames in the sequence. The transformer encodes object features from all frames, and uses trajectory queries to group them into trajectories. The trajectory queries are object features from a single frame and naturally produce unique trajectories.

2022: Xingyi Zhou, Tianwei Yin, V. Koltun, Phillip Krahenbuhl

Ranked #4 on Multi-Object Tracking on MOT17

https://arxiv.org/pdf/2203.13250v1.pdf