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| # SV3D-diffusers | |
|  | |
| This repo 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). | |
| ## 🔥 See Also | |
| You may also be interested in our works: | |
| - [**[ICLR 2025] DiffSplat**](https://github.com/chenguolin/DiffSplat): generate 3D objects in 3DGS directly by fine-tuning a text-to-image models. | |
| - [**[NeurIPS 2024] HumanSplat**](https://github.com/humansplat/humansplat): SV3D is fine-tuned on human datasets for single-view human reconstruction. | |
| ## 🚀 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)** |  |  |  | | |
| | **Official SV3D** |  |  |  | | |
| ## 📚 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}, | |
| } | |
| ``` | |