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arXiv Computer Vision By Fabian G\"ulhan, Emil Mededovic, Yuli Wu, Johannes Stegmaier

SelfMOTR: Revisiting MOTR with Self-Generating Detection Priors

Read the original on arXiv Computer Vision →

SelfMOTR proposes a detector‑free approach to multi‑object tracking that decouples proposal discovery from association by generating internal detection priors. The method builds on end‑to‑end transformer trackers, showing that joint detection‑association decoding retains hidden detection capacity and can be leveraged without external detectors. Experiments demonstrate competitive results, achieving 69.2 HOTA on DanceTrack and 71.1 HOTA on Bird Flock Tracking.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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