Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis
Published: Aug 1, 2019
Abstract
Developing conditional generative models for text-to-video synthesis is an extremely challenging yet an important topic of research in machine learning. In this work, we address this problem by introducing Text-Filter conditioning Generative Adversarial Network (TFGAN), a conditional GAN model with a novel multi-scale text-conditioning scheme that improves text-video associations. By combining the proposed conditioning scheme with a deep GAN...
Paper Details
Title
Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis
Published Date
Aug 1, 2019
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