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

Ming Ding · Wendi Zheng · Wenyi Hong · Jie Tang

Hall J (level 1) #925

Keywords: [ text-to-image generation ] [ pretraining ] [ transformer ]


Development of transformer-based text-to-image models is 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 autoregressive generation. We pretrain a 6B-parameter transformer with a simple and flexible self-supervised task, a cross-modal general language model (CogLM), and fine-tune 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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