VG-CGARN: Video Generation Using Convolutional Generative Adversarial and Recurrent Networks

Generating dynamic videos from static images and accurately modeling object motion within scenes are fundamental challenges in computer vision, with broad applications in video enhancement, photo animation, and visual scene understanding. This paper proposes a novel hybrid framework that combines co...

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Bibliographic Details
Main Authors: Fatemeh Sobhani Manesh, Amin Nazari, Muharram Mansoorizadeh, MirHossein Dezfoulian
Format: Article
Language:English
Published: University of science and culture 2025-04-01
Series:International Journal of Web Research
Subjects:
Online Access:https://ijwr.usc.ac.ir/article_221691_14280a8d79682e6da4ec6512fb2d9842.pdf
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