--- license: other license_name: sv3d-nc-community license_link: LICENSE datasets: - allenai/objaverse pipeline_tag: image-to-video extra_gated_prompt: >- By clicking "Agree", you agree to the [License Agreement](https://huggingface.co/stabilityai/sv3d/blob/main/LICENSE.md) and acknowledge Stability AI's [Privacy Policy](https://stability.ai/privacy-policy). extra_gated_fields: Name: text Email: text Country: country Organization or Affiliation: text Receive email updates and promotions on Stability AI products, services, and research?: type: select options: - Yes - No --- # [SV3D-diffusers](https://github.com/chenguolin/sv3d-diffusers) ![](assets/sv3doutputs.gif) This repo (https://github.com/chenguolin/sv3d-diffusers) provides scripts about: 1. Spatio-temporal UNet (`SV3DUNetSpatioTemporalConditionModel`) and pipeline (`StableVideo3DDiffusionPipeline`) modified from [SVD](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_video_diffusion/pipeline_stable_video_diffusion.py) for [SV3D](https://sv3d.github.io) in the [diffusers](https://github.com/huggingface/diffusers) convention. 2. Converting the [Stability-AI](https://github.com/Stability-AI/generative-models)'s [SV3D-p UNet checkpoint](https://huggingface.co/stabilityai/sv3d) to the [diffusers](https://github.com/huggingface/diffusers) convention. 3. Infering the `SV3D-p` model with the [diffusers](https://github.com/huggingface/diffusers) library to synthesize a 21-frame orbital video around a 3D object from a single-view image (preprocessed by removing background and centering first). Converted SV3D-p checkpoints have been uploaded to HuggingFace🤗 [chenguolin/sv3d-diffusers](https://huggingface.co/chenguolin/sv3d-diffusers). ## 🚀 Usage ```bash git clone https://github.com/chenguolin/sv3d-diffusers.git # Please install PyTorch first according to your CUDA version pip3 install -r requirements.txt # If you can't access to HuggingFace🤗, try: # export HF_ENDPOINT=https://hf-mirror.com python3 infer.py --output_dir out/ --image_path assets/images/sculpture.png --elevation 10 --half_precision --seed -1 ``` The synthesized video will save at `out/` as a `.gif` file. ## 📸 Results > Image preprocessing and random seed for different implementations are different, so the results are presented only for reference. | Implementation | sculpture | bag | kunkun | | :------------- | :------: | :----: | :----: | | **SV3D-diffusers (Ours)** | ![](assets/sculpture.gif) | ![](assets/bag.gif) | ![](assets/kunkun.gif) | | **Official SV3D** | ![](assets/sculpture_official.gif) | ![](assets/bag_official.gif) | ![](assets/kunkun_official.gif) | ## 📚 Citation If you find this repo helpful, please consider giving this repository a star 🌟 and citing the original SV3D paper. ``` @inproceedings{voleti2024sv3d, author={Voleti, Vikram and Yao, Chun-Han and Boss, Mark and Letts, Adam and Pankratz, David and Tochilkin, Dmitrii and Laforte, Christian and Rombach, Robin and Jampani, Varun}, title={{SV3D}: Novel Multi-view Synthesis and {3D} Generation from a Single Image using Latent Video Diffusion}, booktitle={European Conference on Computer Vision (ECCV)}, year={2024}, } ```