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Ioannis Pitas (AUTH)
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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. 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 revolutionise arts and media production.
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