CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers
2022-04-28Code Available2· sign in to hype
Ming Ding, Wendi Zheng, Wenyi Hong, Jie Tang
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ReproduceCode
- github.com/thudm/cogview2OfficialIn paperpytorch★ 955
Abstract
The development of the transformer-based text-to-image models are impeded by its slow generation and complexity for high-resolution images. In this work, we put forward a solution based on hierarchical transformers and local parallel auto-regressive generation. We pretrain a 6B-parameter transformer with a simple and flexible self-supervised task, Cross-modal general language model (CogLM), and finetune it for fast super-resolution. The new text-to-image system, CogView2, shows very competitive generation compared to concurrent state-of-the-art DALL-E-2, and naturally supports interactive text-guided editing on images.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| COCO (Common Objects in Context) | CogView2(6B, Finetuned) | FID | 17.7 | — | Unverified |
| COCO (Common Objects in Context) | CogView2(6B, Finetuned) | FID | 24 | — | Unverified |