24 citations · 29 across the 3 of their papers we have counts for
6 papers · 1 filter
Depth-based Privileged Information for Boosting 3D Human Pose Estimation on RGB
Alessandro Simoni, Francesco Marchetti, Guido Borghi +6
Despite the recent advances in computer vision research, estimating the 3D human pose from single RGB images remains a challenging task, as multiple 3D poses can correspond to the…
Robust Action Segmentation from Timestamp Supervision
Yaser Souri, Yazan Abu Farha, Emad Bahrami +2
Action segmentation is the task of predicting an action label for each frame of an untrimmed video. As obtaining annotations to train an approach for action segmentation in a fully…
FIFA: Fast Inference Approximation for Action Segmentation
Yaser Souri, Yazan Abu Farha, Fabien Despinoy +2
We introduce FIFA, a fast approximate inference method for action segmentation and alignment. Unlike previous approaches, FIFA does not rely on expensive dynamic programming for in…
UNIK: A Unified Framework for Real-world Skeleton-based Action Recognition
Di Yang, Yaohui Wang, Antitza Dantcheva +3
Action recognition based on skeleton data has recently witnessed increasing attention and progress. State-of-the-art approaches adopting Graph Convolutional networks (GCNs) can eff…
Selective Spatio-Temporal Aggregation Based Pose Refinement System: Towards Understanding Human Activities in Real-World Videos
Di Yang, Rui Dai, Yaohui Wang +4
Taking advantage of human pose data for understanding human activities has attracted much attention these days. However, state-of-the-art pose estimators struggle in obtaining high…
Deep-Temporal LSTM for Daily Living Action Recognition
Srijan Das, Michal Koperski, Francois Bremond +1
In this paper, we propose to improve the traditional use of RNNs by employing a many to many model for video classification. We analyze the importance of modeling spatial layout an…