15 citations · 30 across the 5 of their papers we have counts for
9 papers
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…
Multi-Modal Temporal Convolutional Network for Anticipating Actions in Egocentric Videos
Olga Zatsarynna, Yazan Abu Farha, Juergen Gall
Anticipating human actions is an important task that needs to be addressed for the development of reliable intelligent agents, such as self-driving cars or robot assistants. While…
Temporal Action Segmentation from Timestamp Supervision
Zhe Li, Yazan Abu Farha, Juergen Gall
Temporal action segmentation approaches have been very successful recently. However, annotating videos with frame-wise labels to train such models is very expensive and time consum…
Pose Refinement Graph Convolutional Network for Skeleton-based Action Recognition
Shijie Li, Jinhui Yi, Yazan Abu Farha +1
With the advances in capturing 2D or 3D skeleton data, skeleton-based action recognition has received an increasing interest over the last years. As skeleton data is commonly repre…
Long-Term Anticipation of Activities with Cycle Consistency
Yazan Abu Farha, Qiuhong Ke, Bernt Schiele +1
With the success of deep learning methods in analyzing activities in videos, more attention has recently been focused towards anticipating future activities. However, most of the w…
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation
Shijie Li, Yazan Abu Farha, Yun Liu +2
With the success of deep learning in classifying short trimmed videos, more attention has been focused on temporally segmenting and classifying activities in long untrimmed videos.…