Learning Unsupervised Visual Representations using 3D Convolutional Autoencoder with Temporal Contrastive Modeling for Video Retrieval

The rapid growth of tag-free user-generated videos (on the Internet), surgical recorded videos, and surveillance videos has necessitated the need for effective content-based video retrieval systems. Earlier methods for video representations are based on hand-crafted, which hardly performed well on t...

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Vydané v:	International journal of mathematical, engineering and management sciences Ročník 7; číslo 2; s. 272 - 287
Hlavní autori:	Kumar, Vidit, Tripathi, Vikas, Pant, Bhaskar
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Dehradun International Journal of Mathematical, Engineering and Management Sciences 01.04.2022 Ram Arti Publishers
Predmet:	content-based search contrastive learning convolutional autoencoder Datasets Deep learning future prediction Teaching methods unsupervised learning User generated content video retrieval India
ISSN:	2455-7749, 2455-7749
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