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Paper page - CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
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https://github.com/THUDM/CogVideo

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Question from the community \n\n@tengjiayan\n\t \n\n@keg-yzy\n\t \n\n@zwd125\n\t:
Plz ask them if they or someone can make it available in Open WebUI via ComfyUI, Auto1111 or other methods to run it locally on our machines

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Papers
arxiv:2408.06072

CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Published on Aug 12, 2024
ยท Submitted by
AK
on Aug 13, 2024

Abstract

CogVideoX is a large-scale diffusion transformer model using a 3D Variational Autoencoder and expert transformer for generating high-quality, coherent videos from text prompts.

AI-generated summary

We introduce CogVideoX, a large-scale diffusion transformer model designed for generating videos based on text prompts. To efficently model video data, we propose to levearge a 3D Variational Autoencoder (VAE) to compress videos along both spatial and temporal dimensions. To improve the text-video alignment, we propose an expert transformer with the expert adaptive LayerNorm to facilitate the deep fusion between the two modalities. By employing a progressive training technique, CogVideoX is adept at producing coherent, long-duration videos characterized by significant motions. In addition, we develop an effective text-video data processing pipeline that includes various data preprocessing strategies and a video captioning method. It significantly helps enhance the performance of CogVideoX, improving both generation quality and semantic alignment. Results show that CogVideoX demonstrates state-of-the-art performance across both multiple machine metrics and human evaluations. The model weights of both the 3D Causal VAE and CogVideoX are publicly available at https://github.com/THUDM/CogVideo.

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