1 citations · 1 across the 6 of their papers we have counts for
11 papers · 1 filter
Action Segmentation Using 2D Skeleton Heatmaps and Multi-Modality Fusion
Syed Waleed Hyder, Muhammad Usama, Anas Zafar +5
This paper presents a 2D skeleton-based action segmentation method with applications in fine-grained human activity recognition. In contrast with state-of-the-art methods which dir…
Learning by Aligning 2D Skeleton Sequences and Multi-Modality Fusion
Quoc-Huy Tran, Muhammad Ahmed, Murad Popattia +3
This paper presents a self-supervised temporal video alignment framework which is useful for several fine-grained human activity understanding applications. In contrast with the st…
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…
Timestamp-Supervised Action Segmentation with Graph Convolutional Networks
Hamza Khan, Sanjay Haresh, Awais Ahmed +4
We introduce a novel approach for temporal activity segmentation with timestamp supervision. Our main contribution is a graph convolutional network, which is learned in an end-to-e…
Unsupervised Action Segmentation by Joint Representation Learning and Online Clustering
Sateesh Kumar, Sanjay Haresh, Awais Ahmed +3
We present a novel approach for unsupervised activity segmentation which uses video frame clustering as a pretext task and simultaneously performs representation learning and onlin…
Learning by Aligning Videos in Time
Sanjay Haresh, Sateesh Kumar, Huseyin Coskun +4
We present a self-supervised approach for learning video representations using temporal video alignment as a pretext task, while exploiting both frame-level and video-level informa…