3 papers
cs.CV2026
Unsupervised Skeleton-Based Action Segmentation via Hierarchical Spatiotemporal Vector Quantization
Umer Ahmed, Syed Ahmed Mahmood, Fawad Javed Fateh +3
We propose a novel hierarchical spatiotemporal vector quantization framework for unsupervised skeleton-based temporal action segmentation. We first introduce a hierarchical approac…
cs.CV2025
Procedure Learning via Regularized Gromov-Wasserstein Optimal Transport
Syed Ahmed Mahmood, Ali Shah Ali, Umer Ahmed +3
We study self-supervised procedure learning, which discovers key steps and their order from a set of unlabeled videos. Previous methods typically learn frame-to-frame correspondenc…
cs.CV2025
Joint Self-Supervised Video Alignment and Action Segmentation
Ali Shah Ali, Syed Ahmed Mahmood, Mubin Saeed +3
We introduce a novel approach for simultaneous self-supervised video alignment and action segmentation based on a unified optimal transport framework. In particular, we first tackl…