Creating Videos from Images
Explore advanced methods to create realistic talking head videos from a minimal number of images. Understand how generative adversarial networks and few-shot learning enable personalized video synthesis, even from single photos, by capturing complex facial features and dynamic movements.
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GANs can generate novel photorealistic images after being trained on a group of example photos. This technique can also be used to create variations of an image, either by applying “filters” or new poses or angles of the base image.
Limitations
Could we push this approach to its utmost potential and generate a talking head from just one or a few images? This task presents a significant challenge. Traditional methods, including deep learning techniques, often introduce noticeable artifacts when applying “warping”
Despite recent advances in convolutional neural networks (CNNs) capable of generating highly realistic human head images, these models typically necessitate training on extensive datasets portraying a single individual to establish a personalized talking head model. However, practical scenarios frequently require the creation of such models with limited input, possibly just a few image views or even a single ...