Semantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesis

21 Nov 2019 Ceyuan Yang Yujun Shen Bolei Zhou

Despite the success of Generative Adversarial Networks (GANs) in image synthesis, there lacks enough understanding on what generative models have learned inside the deep generative representations and how photo-realistic images are able to be composed of the layer-wise stochasticity introduced in recent GANs. In this work, we show that highly-structured semantic hierarchy emerges as variation factors from synthesizing scenes from the generative representations in state-of-the-art GAN models, like StyleGAN and BigGAN... (read more)

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