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What is Hierarchical GAN for Text-to-Image Synthesis about?

This paper presents a novel method for generating photographic images conditioned on text descriptions using a hierarchically-nested adversarial network. The method introduces accompanying discriminators at multiple scales in the generator network to regularize mid-level representations and assist training. An extensive convolutional generator architecture and multi-purpose adversarial loss are used to improve semantic consistency and image fidelity. The method is validated on three datasets and shown to ou

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