Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Gungor, Cagri"'
Autor:
Gungor, Cagri, Kovashka, Adriana
While motion has garnered attention in various tasks, its potential as a modality for weakly-supervised object detection (WSOD) in static images remains unexplored. Our study introduces an approach to enhance WSOD methods by integrating motion inform
Externí odkaz:
http://arxiv.org/abs/2409.09616
Autor:
Gungor, Cagri, Kovashka, Adriana
First-person activity recognition is rapidly growing due to the widespread use of wearable cameras but faces challenges from domain shifts across different environments, such as varying objects or background scenes. We propose a multimodal framework
Externí odkaz:
http://arxiv.org/abs/2409.09611
Autor:
Gungor, Cagri, Kovashka, Adriana
Despite recent attention and exploration of depth for various tasks, it is still an unexplored modality for weakly-supervised object detection (WSOD). We propose an amplifier method for enhancing the performance of WSOD by integrating depth informati
Externí odkaz:
http://arxiv.org/abs/2303.10937
Publikováno v:
In Computers and Electrical Engineering February 2016 50:79-90
Publikováno v:
2014 21st International Conference on Telecommunications (ICT); 2014, p277-282, 6p