Zobrazeno 1 - 10
of 348
pro vyhledávání: '"Bremond, Francois"'
Deep learning models, in particular \textit{image} models, have recently gained generalisability and robustness. %are becoming more general and robust by the day. In this work, we propose to exploit such advances in the realm of \textit{video} classi
Externí odkaz:
http://arxiv.org/abs/2411.02065
Current vision-language foundation models, such as CLIP, have recently shown significant improvement in performance across various downstream tasks. However, whether such foundation models significantly improve more complex fine-grained action recogn
Externí odkaz:
http://arxiv.org/abs/2410.17149
Autor:
Ali, Abid, Dai, Rui, Marisetty, Ashish, Astruc, Guillaume, Thonnat, Monique, Odobez, Jean-Marc, Thümmler, Susanne, Bremond, Francois
Publikováno v:
IEEE/CVF Winter Conference on Applications of Computer Vision 2025
The computer vision community has explored dyadic interactions for atomic actions such as pushing, carrying-object, etc. However, with the advancement in deep learning models, there is a need to explore more complex dyadic situations such as loose in
Externí odkaz:
http://arxiv.org/abs/2409.20270
Autor:
Stanczyk, Tomasz, Bremond, Francois
Multi-object tracking (MOT) involves identifying and consistently tracking objects across video sequences. Traditional tracking-by-detection methods, while effective, often require extensive tuning and lack generalizability. On the other hand, segmen
Externí odkaz:
http://arxiv.org/abs/2409.14220
Temporal Action Detection (TAD), the task of localizing and classifying actions in untrimmed video, remains challenging due to action overlaps and variable action durations. Recent findings suggest that TAD performance is dependent on the structural
Externí odkaz:
http://arxiv.org/abs/2409.04205
Autor:
Müller, Philipp, Balazia, Michal, Baur, Tobias, Dietz, Michael, Heimerl, Alexander, Penzkofer, Anna, Schiller, Dominik, Brémond, François, Alexandersson, Jan, André, Elisabeth, Bulling, Andreas
Estimating the momentary level of participant's engagement is an important prerequisite for assistive systems that support human interactions. Previous work has addressed this task in within-domain evaluation scenarios, i.e. training and testing on t
Externí odkaz:
http://arxiv.org/abs/2408.16625
Video anomaly detection (VAD) in autonomous driving scenario is an important task, however it involves several challenges due to the ego-centric views and moving camera. Due to this, it remains largely under-explored. While recent developments in wea
Externí odkaz:
http://arxiv.org/abs/2408.05562
Autor:
Ali, Abid, Ali, Mahmoud, Odobez, Jean-Marc, Barbini, Camilla, Dubuisson, Séverine, Bremond, Francois, Thümmler, Susanne
Autism Spectrum Disorder (ASD) is a diverse collection of neurobiological conditions marked by challenges in social communication and reciprocal interactions, as well as repetitive and stereotypical behaviors. Atypical behavior patterns in a long, un
Externí odkaz:
http://arxiv.org/abs/2407.09159
Autor:
Chakraborty, Rajatsubhra, Sinha, Arkaprava, Reilly, Dominick, Govind, Manish Kumar, Wang, Pu, Bremond, Francois, Das, Srijan
Large Language Vision Models (LLVMs) have demonstrated effectiveness in processing internet videos, yet they struggle with the visually perplexing dynamics present in Activities of Daily Living (ADL) due to limited pertinent datasets and models tailo
Externí odkaz:
http://arxiv.org/abs/2406.09390
Publikováno v:
WACV 2024
Age estimation is a challenging task that has numerous applications. In this paper, we propose a new direction for age classification that utilizes a video-based model to address challenges such as occlusions, low-resolution, and lighting conditions.
Externí odkaz:
http://arxiv.org/abs/2311.02432