Fast Self-Supervised Depth and Mask Aware Association for Multi-Object Tracking
The paper “Fast Self-Supervised Depth and Mask Aware Association for Multi-Object Tracking” by Milad Khanchi, Maria Amer, and Charalambos Poullis has been accepted for publication at British Machine Vision Conference (BMVC) 2025.
TL;DR: SelfTrEncMOT is a novel multi-object tracking framework that integrates zero-shot monocular depth estimation and promptable segmentation