Generative Adversarial Networks in Multimedia Content Creation
Deep Convolutional Generative Adversarial Networks (DCGAN) have been used to generate highly compelling pictures or videos, such as manipulated facial animations, interior and outdoor images, videos.

Short Summary
This lecture provides an extensive overview of several Generative Adversarial Networks applications for media production, notably for image content generation (e.g., human facial and body images), automatic image restyling/translation/captioning, text to image synthesis, video frame prediction, video content generation (e.g., human animations), automatic audio-visual content captioning. If this trend does indeed succeed, it will revolutionize arts and media production.
Pace
Self-paced
Language
English
Country
Greece
Credits
No
Subject Categories
Machine learning
Business Categories
Public Services
Last updated
Wed, 07/05/2023 - 14:44