Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Tur, Anil Osman"'
Autor:
Tur, Anil Osman, Conti, Alessandro, Beyan, Cigdem, Boscaini, Davide, Larcher, Roberto, Messelodi, Stefano, Poiesi, Fabio, Ricci, Elisa
In smart retail applications, the large number of products and their frequent turnover necessitate reliable zero-shot object classification methods. The zero-shot assumption is essential to avoid the need for re-training the classifier every time a n
Externí odkaz:
http://arxiv.org/abs/2409.14963
This paper aims to address the unsupervised video anomaly detection (VAD) problem, which involves classifying each frame in a video as normal or abnormal, without any access to labels. To accomplish this, the proposed method employs conditional diffu
Externí odkaz:
http://arxiv.org/abs/2307.01533
This paper investigates the performance of diffusion models for video anomaly detection (VAD) within the most challenging but also the most operational scenario in which the data annotations are not used. As being sparse, diverse, contextual, and oft
Externí odkaz:
http://arxiv.org/abs/2304.05841
Autor:
Tur, Anil Osman, Keles, Hacer Yalim
Isolated sign recognition from video streams is a challenging problem due to the multi-modal nature of the signs, where both local and global hand features and face gestures needs to be attended simultaneously. This problem has recently been studied
Externí odkaz:
http://arxiv.org/abs/2006.11183
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.