15 citations · 33 across the 11 of their papers we have counts for
15 papers · 1 filter
Looking into the Unknown: Exploring Action Discovery for Segmentation of Known and Unknown Actions
Federico Spurio, Emad Bahrami, Olga Zatsarynna +3
We introduce Action Discovery, a novel setup within Temporal Action Segmentation that addresses the challenge of defining and annotating ambiguous actions and incomplete annotation…
MANTA: Diffusion Mamba for Efficient and Effective Stochastic Long-Term Dense Anticipation
Olga Zatsarynna, Emad Bahrami, Yazan Abu Farha +2
Long-term dense action anticipation is very challenging since it requires predicting actions and their durations several minutes into the future based on provided video observation…
Gated Temporal Diffusion for Stochastic Long-Term Dense Anticipation
Olga Zatsarynna, Emad Bahrami, Yazan Abu Farha +2
Long-term action anticipation has become an important task for many applications such as autonomous driving and human-robot interaction. Unlike short-term anticipation, predicting…
Rethinking temporal self-similarity for repetitive action counting
Yanan Luo, Jinhui Yi, Yazan Abu Farha +2
Counting repetitive actions in long untrimmed videos is a challenging task that has many applications such as rehabilitation. State-of-the-art methods predict action counts by firs…
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…
Self-supervised Learning for Unintentional Action Prediction
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 syst…