Video Depth Anything Small
This repository contains the model described in Video Depth Anything: Consistent Depth Estimation for Super-Long Videos.
Model source
- Kind
- Other
- File size
- 111 MB
- Version
- vRevision 2568753
- Updated
- Nov 1, 2026
- Downloads
- 0
- Source
- Hugging Face
Source description
Video Depth Anything
This repository contains the model described in Video Depth Anything: Consistent Depth Estimation for Super-Long Videos.
Project Page: https://videodepthanything.github.io
About
This model is based on Depth Anything V2, and can be applied to arbitrarily long videos without compromising quality, consistency, or generalization ability. Compared with other diffusion-based models, it enjoys faster inference speed, fewer parameters, and higher consistent depth accuracy.
Usage
git clone https://github.com/DepthAnything/Video-Depth-Anything
cd Video-Depth-Anything
pip install -r requirements.txt
Download the checkpoints listed here and put them under the checkpoints directory.
bash get_weights.sh
Inference a video
python3 run.py --input_video ./assets/example_videos/davis_rollercoaster.mp4 --output_dir ./outputs --encoder vitl
Sources
1 source
Sources
1 sourceVerified Nov 1
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
2 excerpts
Source excerpts
2 excerpts--- license: apache-2.0 library_name: pytorch pipeline_tag: depth-estimation --- # Video Depth Anything This repository contains the model described in [Video Depth Anything: Consistent Depth Estimation for Super-Long Videos](https://huggingface.co/papers/2501.12375). Project Page: https://videodepthanything.github.io ## About This model is based on [Depth Anything V2](https://github.com/DepthAnything/Depth-Anything-V2), and can be applied to arbitrarily long videos without compromising quality, consistency, or generalization ability. Compared with other diffusion-based models, it enjoys faster inference speed, fewer parameters, and higher consistent depth accuracy. ## Usage ```bash git clone https://github.com/DepthAnything/Video-Depth-Anything cd Video-Depth-Anything pip install -r requirements.txt ``` Download the checkpoints listed [here](#pre-trained-models) and put them under the `checkpoints` directory. ```bash bash get_weights.sh ``` ### Inference a video ```bash python3 run.py --input_video ./assets/example_videos/davis_rollercoaster.mp4 --output_dir ./outputs --encoder vitl ```
Source context: 0 downloads · 11 likes · Pipeline depth-estimation · Library pytorch · Repo depth-anything/Video-Depth-Anything-Small
