Exciting developments in GANs have led to the creation of photorealistic images, pushing the boundaries of applied deep learning. New frameworks, like neural rendering models, are being explored to enhance semi-supervised learning by integrating generative processes directly into convolutional networks, capturing relevant hidden variables and uncertainties for improved outcomes.
