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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Official repo for VGen: a holistic video generation ecosystem for video generation building on diffusion models
| Date | Stars |
|---|---|
| 2026-07-31 | 3156 |
| 2026-08-03 | 3156 |
| 2026-08-06 | 3156 |
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growth rate 0.00%/day
# VGen  VGen is an open-source video synthesis codebase developed by the Tongyi Lab of Alibaba Group, featuring state-of-the-art video generative models. This repository includes implementations of the following methods: - [I2VGen-xl: High-quality image-to-video synthesis via cascaded diffusion models](https://i2vgen-xl.github.io) - [VideoComposer: Compositional Video Synthesis with Motion Controllability](https://videocomposer.github.io) - [Hierarchical Spatio-temporal Decoupling for Text-to-Video Generation](https://higen-t2v.github.io) - [A Recipe for Scaling up Text-to-Video Generation with Text-free Videos](https://tf-t2v.github.io) - [InstructVideo: Instructing Video Diffusion Models with Human Feedback](https://instructvideo.github.io) - [DreamVideo: Composing Your Dream Videos with Customized Subject and Motion](https://dreamvideo-t2v.github.io) - [VideoLCM: Video Latent Consistency Model](https://arxiv.org/abs/2312.09109) - [Modelscope text-to-video technical report](https://arxiv.org/abs/2308.06571) VGen can produce high-quality videos from the input text, images, desired motion, desired subjects, and even the feedback signals provided. It also offers a variety of commonly used video generation tools such as visualization, sampling, training, inference, join training using images and videos, acceleration, and more. <a href='https://i2vgen-xl.github.io/'><img src='https://img.shields.io/badge/Project-Page-Green'></a> <a href='https://arxiv.org/abs/2311.04145'><img src='https://img.shields.io/badge/Paper-Arxiv-red'></a> [](https://huggingface.co/spaces/damo-vilab/I2VGen-XL) [](https://huggingface.co/papers/2311.04145) [](https://huggingface.co/spaces/damo-vilab/I2VGen-XL/discussions) [](https://youtu.be/XUi0y7dxqEQ) <a href='https://cloud.video.taobao.com/play/u/null/p/1/e/6/t/1/441039979087.mp4'><img src='source/logo.png'></a> [](https://replicate.com/cjwbw/i2vgen-xl/) ## 🔥News!!! - __[2025.01]__ We release the code for [metric calculation](./metric/README.MD) used in DreamVideo (**CLIP-T**, **CLIP-I**, **DINO-I**, and **Temporal Consistency**). - __[2024.06]__ We release the code and models of [InstructVideo](https://instructvideo.github.io/). InstructVideo enables the **LoRA** fine-tuning and inference in VGen. Feel free to use LoRA fine-tuning for other tasks. - __[2024.04]__ We release the models of [DreamVideo](https://dreamvideo-t2v.github.io) and ModelScopeT2V V1.5!!! ModelScopeT2V V1.5 is further fine-tuned on ModelScopeT2V for 365k iterations with more data. - __[2024.04]__ We release the code and models of [TF-T2V](https://tf-t2v.github.io)! - __[2024.04]__ We release the code and models of [VideoLCM](https://tf-t2v.github.io)! - __[2024.03]__ We release the training and inference code of [DreamVideo](https://dreamvideo-t2v.github.io)! - __[2024.03]__ We release the code and model of HiGen!! - __[2024.01]__ The gradio demo of I2VGen-XL has been completed in [HuggingFace](https://huggingface.co/spaces/damo-vilab/I2VGen-XL), thanks to our colleague @[Wenmeng Zhou](https://github.com/wenmengzhou) and @[AK](https://twitter.com/_akhaliq) for the support, and welcome to try it out. - __[2024.01]__ We support running the gradio app locally, thanks to our colleague @[Wenmeng Zhou](https://github.com/wenmengzhou) for the support and @[AK](https://twitter.com/_akhaliq) for the suggestion, and welcome to have a try. - __[2024.01]__ Thanks @[Chenxi](https://chenxwh.github.io) for supporting the running of i2vgen-xl on [
Shiwei Zhang · Alibaba Group
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qinzhi · hust
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Hangjie Yuan · ZJU, Alibaba DAMO, MMLab@NTU · Singapore
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Xinliang Dai · @Alibaba · China
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Chenxi
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kish
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:f70267d130324d1a, topic:diffusion-models