no code implementations • 12 Oct 2022 • Yaser Souri, Yazan Abu Farha, Emad Bahrami, Gianpiero Francesca, Juergen Gall
As obtaining annotations to train an approach for action segmentation in a fully supervised way is expensive, various approaches have been proposed to train action segmentation models using different forms of weak supervision, e. g., action transcripts, action sets, or more recently timestamps.
no code implementations • 24 Sep 2022 • Olga Zatsarynna, Yazan Abu Farha, Juergen Gall
Distinguishing if an action is performed as intended or if an intended action fails is an important skill that not only humans have, but that is also important for intelligent systems that operate in human environments.
no code implementations • 9 Aug 2021 • Yaser Souri, Yazan Abu Farha, Fabien Despinoy, Gianpiero Francesca, Juergen Gall
We apply FIFA on top of state-of-the-art approaches for weakly supervised action segmentation and alignment as well as fully supervised action segmentation.
Segmentation Weakly Supervised Action Segmentation (Transcript)
no code implementations • 18 Jul 2021 • Olga Zatsarynna, Yazan Abu Farha, Juergen Gall
This poses a problem for domains such as autonomous driving, where the reaction time is crucial.
Ranked #8 on Action Anticipation on EPIC-KITCHENS-100 (test)
1 code implementation • CVPR 2021 • Zhe Li, Yazan Abu Farha, Juergen Gall
To demonstrate the effectiveness of timestamp supervision, we propose an approach to train a segmentation model using only timestamps annotations.
Ranked #4 on Weakly Supervised Action Localization on GTEA
no code implementations • 14 Oct 2020 • Shijie Li, Jinhui Yi, Yazan Abu Farha, Juergen Gall
To this end, the network first refines the poses before they are further processed to recognize the action.
no code implementations • 2 Sep 2020 • Yazan Abu Farha, Qiuhong Ke, Bernt Schiele, Juergen Gall
With the success of deep learning methods in analyzing activities in videos, more attention has recently been focused towards anticipating future activities.
1 code implementation • 16 Jun 2020 • Shijie Li, Yazan Abu Farha, Yun Liu, Ming-Ming Cheng, Juergen Gall
Despite the capabilities of these approaches in capturing temporal dependencies, their predictions suffer from over-segmentation errors.
Ranked #5 on Action Segmentation on Assembly101
no code implementations • 26 Aug 2019 • Yazan Abu Farha, Juergen Gall
Anticipating future activities in video is a task with many practical applications.
2 code implementations • CVPR 2019 • Yazan Abu Farha, Juergen Gall
Temporally locating and classifying action segments in long untrimmed videos is of particular interest to many applications like surveillance and robotics.
Ranked #20 on Action Segmentation on GTEA
1 code implementation • CVPR 2018 • Yazan Abu Farha, Alexander Richard, Juergen Gall
Analyzing human actions in videos has gained increased attention recently.