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pro vyhledávání: '"Javidani, Ali"'
Self-supervised visual representation learning traditionally focuses on image-level instance discrimination. Our study introduces an innovative, fine-grained dimension by integrating patch-level discrimination into these methodologies. This integrati
Externí odkaz:
http://arxiv.org/abs/2310.18651
Autor:
Javidani, Ali, Mahmoudi-Aznaveh, Ahmad
In this paper, a novel video classification method is presented that aims to recognize different categories of third-person videos efficiently. Our motivation is to achieve a light model that could be trained with insufficient training data. With thi
Externí odkaz:
http://arxiv.org/abs/1802.06724
Autor:
Javidani, Ali, Mahmoudi-Aznaveh, Ahmad
In this paper, a new video classification methodology is proposed which can be applied in both first and third person videos. The main idea behind the proposed strategy is to capture complementary information of appearance and motion efficiently by p
Externí odkaz:
http://arxiv.org/abs/1801.00192
Akademický článek
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Autor:
Javidani, Ali, Mahmoudi-Aznaveh, Ahmad
Publikováno v:
Multimedia Tools & Applications; Jan2022, Vol. 81 Issue 3, p3145-3163, 19p
