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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Veröffentlicht in:	International journal of mathematical, engineering and management sciences Jg. 7; H. 2; S. 272 - 287
Hauptverfasser:	Kumar, Vidit, Tripathi, Vikas, Pant, Bhaskar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dehradun International Journal of Mathematical, Engineering and Management Sciences 01.04.2022 Ram Arti Publishers
Schlagworte:	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
Online-Zugang:	Volltext
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