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Large-scale pretrained transformers have created milestones in text (GPT-3)and text-to-image (DALL-E and CogView) generation. Its application to videogeneration is still facing many challenges: The potential huge computation costmakes the training from scratch unaffordable; The scarcity and weak relevanceof text-video datasets hinder the model understanding complex movementsemantics. In this work, we present 9B-parameter transformer CogVideo, trainedby inheriting a pretrained text-to-image model, CogView2. We also proposemulti-frame-rate hierarchical training strategy to better align text and videoclips. As (probably) the first open-source large-scale pretrained text-to-videomodel, CogVideo outperforms all publicly available models at a large margin inmachine and human evaluations.

CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers