Exploring Sparse MoE in GANs for Text-conditioned Image Synthesis

Jiapeng Zhu; Ceyuan Yang; Kecheng Zheng; Yinghao Xu; Zifan Shi; Yifei Zhang; Qifeng Chen; Yujun Shen

doi:10.1109/cvpr52734.2025.01716

CVPR2025顶会

Exploring Sparse MoE in GANs for Text-conditioned Image Synthesis

Jiapeng Zhu, Ceyuan Yang, Kecheng Zheng, Yinghao Xu, Zifan Shi, Yifei Zhang, Qifeng Chen, Yujun Shen

DOI 出版方

2025年份

5顶会引用

摘要

A black and white photo of a dog with big eyes. A steaming plate of classic fried rice with vegetables, eggs. A photo of a colorful sports car, with mountain background. Oil painting of a flower garden, distant cottage, soft sunlight. Sunrise over the clouds in the mountains. A pencil sketch of a woman with deep, almond-shaped eyes in. A coral reef with starfish, sea anemones and fish. Figure 1. Example results at 512×512 resolution synthesized by our proposed Aurora, a large-scale GAN-based text-to-image generator.