Zum Inhalt springen
ModelAufgelistetExtern
Herunterladen

ChronoDepth v1

This model represents the official checkpoint of the paper titled "Learning Temporally Consistent Video Depth from Video Diffusion Priors".

ArtUNetBasismodellstabilityai/stable-video-diffusion-img2vid-xtVersionFP16BBewertung

Modellquelle

Art
UNet
Dateigröße
2,84 GB
Basismodell
stabilityai/stable-video-diffusion-img2vid-xt
Version
vFP16
Aktualisiert
1. Nov. 2026
Downloads
78
Quelle
Hugging Face

Quellenbeschreibung

ChronoDepth: Learning Temporally Consistent Video Depth from Video Diffusion Priors

This model represents the official checkpoint of the paper titled "Learning Temporally Consistent Video Depth from Video Diffusion Priors".

Website PaperGitHub

Jiahao Shao*, Yuanbo Yang*, Hongyu Zhou, Youmin Zhang, Yujun Shen, Vitor Guizilini, Yue Wang, Matteo Poggi, Yiyi Liao†

🎓 Citation

Please cite our paper if you find this repository useful:

@misc{shao2024learningtemporallyconsistentvideo,
      title={Learning Temporally Consistent Video Depth from Video Diffusion Priors}, 
      author={Jiahao Shao and Yuanbo Yang and Hongyu Zhou and Youmin Zhang and Yujun Shen and Vitor Guizilini and Yue Wang and Matteo Poggi and Yiyi Liao},
      year={2024},
      eprint={2406.01493},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2406.01493}, 
}

Quellen

1 Quelle
Hugging FacePrimärVersion 8ed51301cb97ec7a61a94a1bff1f7a107f73e9e8
huggingface.co/jhshao/ChronoDepth-v1/tree/8ed51301cb97ec7a61a94a1bff1f7a107f73e9e8

Verifiziert 1. Nov.

Download files

Repository files

File inventory only; completeness is unverified.

Modellartefakte

1 Artefakt

diffusion_pytorch_model.safetensors

safetensors · FP16 (unverified) · 2,84 GB · SHA-256 9b5db40028bf…b469 · Hugging Face

Download file

Quellenauszüge

3 Auszüge

--- license: mit library_name: diffusers pipeline_tag: depth-estimation tags: - video depth estimation base_model: - stabilityai/stable-video-diffusion-img2vid-xt --- # ChronoDepth: Learning Temporally Consistent Video Depth from Video Diffusion Priors This model represents the official checkpoint of the paper titled "Learning Temporally Consistent Video Depth from Video Diffusion Priors". [![Website](https://img.shields.io/website?url=https%3A%2F%2Fjhaoshao.github.io%2FChronoDepth%2F&up_message=ChronoDepth&up_color=blue&style=flat&logo=timescale&logoColor=%23FFDC0F)](https://xdimlab.github.io/ChronoDepth/) [![Paper](https://img.shields.io/badge/arXiv-PDF-b31b1b)](https://arxiv.org/abs/2406.01493)[![GitHub](https://img.shields.io/github/stars/jhaoshao/ChronoDepth?style=default&label=GitHub%20★&logo=github)](https://github.com/jhaoshao/ChronoDepth) [Jiahao Shao*](https://jiahao-shao1.github.io/), Yuanbo Yang*, Hongyu Zhou, [Youmin Zhang](https://youmi-zym.github.io/), [Yujun Shen](https://shenyujun.github.io/), [Vitor Guizilini](https://vitorguizilini.github.io/), [Yue Wang](https://yuewang.xyz/), [Matteo Poggi](https://mattpoggi.github.io/), [Yiyi Liao†](https://yiyiliao.github.io/ ) ## 🎓 Citation Please cite our paper if you find this repository useful: ```bibtex @misc{shao2024learningtemporallyconsistentvideo, title={Learning Temporally Consistent Video Depth from Video Diffusion Priors}, author={Jiahao Shao and Yuanbo Yang and Hongyu Zhou and Youmin Zhang and Yujun Shen and Vitor Guizilini and Yue Wang and Matteo Poggi and Yiyi Liao}, year={2024}, eprint={2406.01493}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2406.01493}, } ```

Source context: 78 downloads · 1 likes · Pipeline depth-estimation · Library diffusers · Repo jhshao/ChronoDepth-v1

Source context: 20 downloads · 1 likes · Pipeline depth-estimation · Library diffusers · Repo jhshao/ChronoDepth-v1