Papers › AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, Xiaodong He
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 subregions of the image by paying attentions to the relevant words in the natural language description. In addition, a deep attentional multimodal similarity model is proposed to compute a fine-grained image-text matching loss for training the generator. The proposed AttnGAN significantly outperforms the previous state of the art, boosting the best reported inception score by 14.14% on the CUB dataset and 170.25% on the more challenging COCO dataset. A detailed analysis is also performed by visualizing the attention layers of the AttnGAN. It for the first time shows that the layered attentional GAN is able to automatically select the condition at the word level for generating different parts of the image.
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Code
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Code Syntology ran Syntology
3 samples harvested; 3 ran; 0 honoured the contract we drafted; 0 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.
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Tasks
1 archive task tag without a task page not shown.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Text-to-Image Generation | CUB | AttnGAN | Inception score | 4.36 | #19 of 20 | Archive leaderboard | report |
| Text-to-Image Generation | MS-COCO | AttnGAN | FID | 35.49 | #1 of 2 | Archive leaderboard | report |
| Text-to-Image Generation | MS-COCO | AttnGAN | Inception score | 25.89 | #1 of 2 | Archive leaderboard | report |
| Text-to-Image Generation | MS-COCO | AttnGAN | SOA-C | 25.88 | #1 of 2 | Archive leaderboard | report |
| Text-to-Image Generation | Multi-Modal-CelebA-HQ | AttnGAN | Acc | 13.0 | #8 of 10 | Archive leaderboard | report |
| Text-to-Image Generation | Multi-Modal-CelebA-HQ | AttnGAN | FID | 125.98 | #8 of 10 | Archive leaderboard | report |
| Text-to-Image Generation | Multi-Modal-CelebA-HQ | AttnGAN | LPIPS | 0.512 | #8 of 10 | Archive leaderboard | report |
| Text-to-Image Generation | Multi-Modal-CelebA-HQ | AttnGAN | Real | 11.9 | #8 of 10 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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