3 papers
cs.RO2026
A Hierarchical Spatiotemporal Action Tokenizer for In-Context Imitation Learning in Robotics
Fawad Javed Fateh, Ali Shah Ali, Murad Popattia +4
We present a novel hierarchical spatiotemporal action tokenizer for in-context imitation learning. We first propose a hierarchical approach, which consists of two successive levels…
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…
cs.CV2025
Permutation-Aware Action Segmentation via Unsupervised Frame-to-Segment Alignment
Quoc-Huy Tran, Ahmed Mehmood, Muhammad Ahmed +4
This paper presents an unsupervised transformer-based framework for temporal activity segmentation which leverages not only frame-level cues but also segment-level cues. This is in…