GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis

Author:

Tao Ming1,Bao Bing-Kun1,Tang Hao2,Xu Changsheng3

Affiliation:

1. Nanjing University of Posts and Telecommunications

2. CVL, ETH Zürich

3. Peng Cheng Laboratory

Publisher

IEEE

Reference60 articles.

1. Gans trained by a two time-scale update rule converge to a local nash equilib-rium;heusel;NeurIPS,0

2. Stack-gan: Text to photorealistic image synthesis with stacked generative adversarial networks;zhang;ICCV,0

3. Vec-tor quantized diffusion model for text-to-image synthesis;gu;CVPR,0

4. Cross-Modal Contrastive Learning for Text-to-Image Generation

5. Cascaded diffusion models for high fidelity image generation;ho;JMLR,2022

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