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Marsil Zakour

7 accepted papers

2025

MistSense: Versatile Online Detection of Procedural and Execution Mistakes

ICCV 2025poster

Online mistake detection is crucial across various domains, ranging from industrial automation to educational applications, as mistakes can be corrected by the human operator after their detection due to the continuous inference on a video stream. While prior research mainly addresses procedural err…

Cited by 0SourcePDFScholar
2024

BoxGrounder: 3D Visual Grounding Using Object Size Estimates

RA-L 2024

Recent advances in simultaneous localization and mapping (SLAM) systems have significantly enhanced the process of creating 3D digital replicas of real-world environments. Numerous applications utilizing these digital twins generally necessitate object-level annotations, which are challenging to acq

Cited by 0SourceScholar
2024

Long-Term Action Anticipation Based on Contextual Alignment

ICASSP 2024accepted

In action anticipation, the model predicts the next future action after a certain observation period. In long-term action anticipation, this idea is further extended to predicting multiple actions and their respective duration. Thus, in this problem setting the model should not only capture relation…

Cited by 0SourceScholar
2024

Rethinking 3D Geometric Object Features for Enhancing Skeleton-based Action Recognition

IROS 2024poster

Human action recognition is crucial for intelligent robots, especially in the realm of human-robot collaboration research. Recent advancements in human pose estimation algorithms have shifted the focus of action recognition towards skeleton-based models, which exhibit robustness to changes in backgr…

Cited by 0SourceScholar
2024

Sim-to-Real Domain Shift in Online Action Detection

IROS 2024poster

Human reasoning comprises the ability to understand and reason about the current action solely based on past information. To provide effective assistance in an eldercare or household environment an assistive robot or intelligent assistive system has to assess human actions correctly. Based on this p…

Cited by 0SourcecodeScholar
2024

TSCL: Timestamp Supervised Contrastive Learning for Action Segmentation

RA-L 2024

Temporal action segmentation is an essential task for understandingcomplex human activity sequences and identifying long-term dependencies between human actions. This is essential for effective non-verbal human-robot collaboration and robotic assistance to understand the underlying human intentions.

Cited by 2SourceScholar
2023

Modeling Action Spatiotemporal Relationships Using Graph-Based Class-Level Attention Network for Long-Term Action Detection

IROS 2023poster

In recent years, Action Detection has become an active research topic in various fields such as human-robot interaction and assistive robots. Most of the previous methods in this field focus on temporally processing the action representation, without considering the dependencies among the action cla…

Cited by 6SourceScholar