| --- |
| tags: |
| - text-to-image |
| - stable-diffusion |
| - audio-to-video |
| language: |
| - en |
| library_name: diffusers |
| --- |
| |
| # V-Express Model Card |
|
|
| <div align="center"> |
|
|
| [**Project Page**](https://tenvence.github.io/p/v-express/) **|** [**Paper**](https://arxiv.org/abs/2406.02511) **|** [**Code**](https://github.com/tencent-ailab/V-Express) |
|
|
| </div> |
|
|
| --- |
|
|
| ## Introduction |
|
|
| ## Models |
|
|
| ### Audio Encoder |
|
|
| - [model_ckpts/wav2vec2-base-960h](https://huggingface.co/tk93/V-Express/tree/main/model_ckpts/wav2vec2-base-960h). (It is also available from the original model card [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h)) |
|
|
| ### Face Analysis |
|
|
| - [model_ckpts/insightface_models/models/buffalo_l](https://huggingface.co/tk93/V-Express/tree/main/model_ckpts/insightface_models/models/buffalo_l). (It is also available from the original repository [insightface/buffalo_l](https://github.com/deepinsight/insightface/releases/download/v0.7/buffalo_l.zip)) |
|
|
| ### V-Express |
|
|
| - [model_ckpts/sd-vae-ft-mse](https://huggingface.co/tk93/V-Express/tree/main/model_ckpts/sd-vae-ft-mse). VAE encoder. (original model card [stabilityai/sd-vae-ft-mse](https://huggingface.co/stabilityai/sd-vae-ft-mse)) |
| - [model_ckpts/stable-diffusion-v1-5](https://huggingface.co/tk93/V-Express/tree/main/model_ckpts/stable-diffusion-v1-5). Only the model configuration file for unet is needed here. (original model card [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5)) |
| - [model_ckpts/v-express](https://huggingface.co/tk93/V-Express/tree/main/model_ckpts/v-express). The video generation model conditional on audio and V-kps we call V-Express. |
| - You should download and put all `.bin` model to `model_ckpts/v-express` directory, which includes `audio_projection.bin`, `denoising_unet.bin`, `motion_module.bin`, `reference_net.bin`, and `v_kps_guider.bin`. |
|
|
| ## licence |
| see [acknowledgements](https://github.com/tencent-ailab/V-Express#acknowledgements) for more information. |
