Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Talavera, Estefania"'
Autor:
Aslam, Asra, Herath, Sachini, Huang, Ziqi, Talavera, Estefania, Bhattacharjee, Deblina, Mittal, Himangi, Staderini, Vanessa, Ren, Mengwei, Farshad, Azade
In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2024, organized alongside the CVPR 2024 in Seattle, Washington, United States. WiCV aims to amplify the voices of underrepresented women in the computer vision communit
Externí odkaz:
http://arxiv.org/abs/2411.02445
The Transformer architecture has shown to be a powerful tool for a wide range of tasks. It is based on the self-attention mechanism, which is an inherently computationally expensive operation with quadratic computational complexity: memory usage and
Externí odkaz:
http://arxiv.org/abs/2402.04239
Video anomaly analysis is a core task actively pursued in the field of computer vision, with applications extending to real-world crime detection in surveillance footage. In this work, we address the task of human-related crime classification. In our
Externí odkaz:
http://arxiv.org/abs/2207.01687
Autor:
Glavan, Andreea, Talavera, Estefania
Indoor scene recognition is a growing field with great potential for behaviour understanding, robot localization, and elderly monitoring, among others. In this study, we approach the task of scene recognition from a novel standpoint, using multi-moda
Externí odkaz:
http://arxiv.org/abs/2112.12409
The automatic detection of anomalies captured by surveillance settings is essential for speeding the otherwise laborious approach. To date, UCF-Crime is the largest available dataset for automatic visual analysis of anomalies and consists of real-wor
Externí odkaz:
http://arxiv.org/abs/2108.00246
Publikováno v:
Neural Comput & Applic (2021)
The field of deep learning is evolving in different directions, with still the need for more efficient training strategies. In this work, we present a novel and robust training scheme that integrates visual explanation techniques in the learning proc
Externí odkaz:
http://arxiv.org/abs/2012.14173
Eating habits are learned throughout the early stages of our lives. However, it is not easy to be aware of how our food-related routine affects our healthy living. In this work, we address the unsupervised discovery of nutritional habits from egocent
Externí odkaz:
http://arxiv.org/abs/2009.07646
The automatic discovery of behaviour is of high importance when aiming to assess and improve the quality of life of people. Egocentric images offer a rich and objective description of the daily life of the camera wearer. This work proposes a new meth
Externí odkaz:
http://arxiv.org/abs/2008.09561
The use of deep learning techniques has exploded during the last few years, resulting in a direct contribution to the field of artificial intelligence. This work aims to be a review of the state-of-the-art in scene recognition with deep learning mode
Externí odkaz:
http://arxiv.org/abs/2007.01806
Publikováno v:
In Pervasive and Mobile Computing October 2023 95
