Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Nguyen, Pha"'
Autor:
Nguyen, Phan The Huy
Problématique : L’édentement et les troubles du sommeil sont des affections chroniques fréquentes chez les personnes âgées et qui peuvent avoir des conséquences défavorables sur le bien-être de ces personnes, ainsi que sur leur qualité de
Externí odkaz:
http://hdl.handle.net/1866/13108
Autor:
Nguyen, PHAM QUYNH YEN
The main goal of this study consists of the development of new asphalt mixes, based on industrial waste materials as replacement of natural aggregates. To achieve this purpose, a new characterisation of these pavements was proposed so to verify that
Video scene graph generation (VidSGG) has emerged as a transformative approach to capturing and interpreting the intricate relationships among objects and their temporal dynamics in video sequences. In this paper, we introduce the new AeroEye dataset
Externí odkaz:
http://arxiv.org/abs/2406.01029
Visual interactivity understanding within visual scenes presents a significant challenge in computer vision. Existing methods focus on complex interactivities while leveraging a simple relationship model. These methods, however, struggle with a diver
Externí odkaz:
http://arxiv.org/abs/2312.03050
HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos
Group Activity Scene Graph (GASG) generation is a challenging task in computer vision, aiming to anticipate and describe relationships between subjects and objects in video sequences. Traditional Video Scene Graph Generation (VidSGG) methods focus on
Externí odkaz:
http://arxiv.org/abs/2312.07740
Group Activity Recognition (GAR) is a fundamental problem in computer vision, with diverse applications in sports video analysis, video surveillance, and social scene understanding. Unlike conventional action recognition, GAR aims to classify the act
Externí odkaz:
http://arxiv.org/abs/2312.00188
Multiple Object Tracking (MOT) aims to find bounding boxes and identities of targeted objects in consecutive video frames. While fully-supervised MOT methods have achieved high accuracy on existing datasets, they cannot generalize well on a newly obt
Externí odkaz:
http://arxiv.org/abs/2306.09613
Autor:
Tran, Kim Hoang, Dinh, Anh Duy Le, Nguyen, Tien Phat, Phan, Thinh, Nguyen, Pha, Luu, Khoa, Adjeroh, Donald, Doretto, Gianfranco, Le, Ngan Hoang
Despite recent significant progress, Multi-Object Tracking (MOT) faces limitations such as reliance on prior knowledge and predefined categories and struggles with unseen objects. To address these issues, Generic Multiple Object Tracking (GMOT) has e
Externí odkaz:
http://arxiv.org/abs/2305.17648
One of the recent trends in vision problems is to use natural language captions to describe the objects of interest. This approach can overcome some limitations of traditional methods that rely on bounding boxes or category annotations. This paper in
Externí odkaz:
http://arxiv.org/abs/2305.13495
Autor:
Chappa, Naga VS Raviteja, Nguyen, Pha, Nelson, Alexander H, Seo, Han-Seok, Li, Xin, Dobbs, Page Daniel, Luu, Khoa
This paper introduces a novel approach to Social Group Activity Recognition (SoGAR) using Self-supervised Transformers network that can effectively utilize unlabeled video data. To extract spatio-temporal information, we created local and global view
Externí odkaz:
http://arxiv.org/abs/2305.06310