AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

• Published in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition pp. 1316 - 1324
• Main Authors: Xu, Tao, Zhang, Pengchuan, Huang, Qiuyuan, Zhang, Han, Gan, Zhe, Huang, Xiaolei, He, Xiaodong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2018
• Subjects: Computational modeling; Gallium nitride; Generative adversarial networks; Generators; Image generation; Semantics; Visualization

In this paper, we propose an Attentional Generative Adversarial Network (AttnGAN) that allows attention-driven, multi-stage refinement for fine-grained text-to-image generation. With a novel attentional generative network, the AttnGAN can synthesize fine-grained details at different sub-regions of t...