Video Depth Anything

Sili Chen · Hengkai Guo^† · Shengnan Zhu · Feihu Zhang
Zilong Huang · Jiashi Feng · Bingyi Kang^†
ByteDance
†Corresponding author

This work presents Video Depth Anything based on Depth Anything V2, which 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.

News

• 2025-02-08: Enable autocast inference. Support grayscale video, NPZ and EXR output formats.
• 2025-01-21: Paper, project page, code, models, and demo are all released.

Release Notes

• 2025-02-08: 🚀🚀🚀 Inference speed and memory usage improvement

  Model	Latency (ms)		GPU VRAM (GB)
  	FP32	FP16	FP32	FP16
  Video-Depth-Anything-V2-Small	9.1	7.5	7.3	6.8
  Video-Depth-Anything-V2-Large	67	14	26.7	23.6

  The Latency and GPU VRAM results are obtained on a single A100 GPU with input of shape 1 x 32 x 518 × 518.

Pre-trained Models

We provide two models of varying scales for robust and consistent video depth estimation:

Model	Params	Checkpoint
Video-Depth-Anything-V2-Small	28.4M	Download
Video-Depth-Anything-V2-Large	381.8M	Download

Usage

Preparation

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

Options:

• --input_video: path of input video
• --output_dir: path to save the output results
• --input_size (optional): By default, we use input size 518 for model inference.
• --max_res (optional): By default, we use maximum resolution 1280 for model inference.
• --encoder (optional): vits for Video-Depth-Anything-V2-Small, vitl for Video-Depth-Anything-V2-Large.
• --max_len (optional): maximum length of the input video, -1 means no limit
• --target_fps (optional): target fps of the input video, -1 means the original fps
• --fp32 (optional): Use fp32 precision for inference. By default, we use fp16.
• --grayscale (optional): Save the grayscale depth map, without applying color palette.
• --save_npz (optional): Save the depth map in npz format.
• --save_exr (optional): Save the depth map in exr format.

Citation

If you find this project useful, please consider citing:

@article{video_depth_anything,
  title={Video Depth Anything: Consistent Depth Estimation for Super-Long Videos},
  author={Chen, Sili and Guo, Hengkai and Zhu, Shengnan and Zhang, Feihu and Huang, Zilong and Feng, Jiashi and Kang, Bingyi}
  journal={arXiv:2501.12375},
  year={2025}
}

LICENSE

Video-Depth-Anything-Small model is under the Apache-2.0 license. Video-Depth-Anything-Large model is under the CC-BY-NC-4.0 license.