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arXiv · 2204.14217

CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers

Ming Ding·Wendi Zheng·Wenyi Hong·Jie Tang
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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.

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Ming Ding, Wendi Zheng, Wenyi Hong, Jie Tang. 2022-04-28. CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers. https://arxiv.org/abs/2204.14217

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