Search Results for author: Yazan Abu Farha

Found 11 papers, 4 papers with code

Robust Action Segmentation from Timestamp Supervision

no code implementations12 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.

Action Segmentation Segmentation

Self-supervised Learning for Unintentional Action Prediction

no code implementations24 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.

Action Classification Representation Learning +1

Temporal Action Segmentation from Timestamp Supervision

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.

Action Segmentation Segmentation +1

Long-Term Anticipation of Activities with Cycle Consistency

no code implementations2 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.

Long Term Anticipation

MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation

1 code implementation16 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.

Action Segmentation Segmentation

Uncertainty-Aware Anticipation of Activities

no code implementations26 Aug 2019 Yazan Abu Farha, Juergen Gall

Anticipating future activities in video is a task with many practical applications.

MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation

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.

Action Segmentation Segmentation

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