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Enforcing Temporal Consistency in Video Depth Estimation, ICCV-W 2021.

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TCMonoDepth: Enforcing Temporal Consistency in Video Depth Estimation

TCMonoDepth is a method for stable depth estimation for any video.

TCMonoDepth 是一个为任意视频估计稳定的深度值的模型。

Paper

Usage

Requirements

  • python
  • pytorch
  • torchvision
  • opencv
  • tqdm

Testing

You can download our pretraind checkppont from link (google drive) or link (百度云, 提取码: w2kr) and save it in the./weights folder. Put your video into the folder videos and run

cd TCMonoDepth
python demo.py --model large --resume ./weights/_ckpt.pt.tar --input ./videos --output ./output --resize_size 384

A small MonoDepth model for mobile devices

A lightweight and very fast monodepth model

cd TCMonoDepth
python demo.py --model small --resume ./weights/_ckpt_small.pt.tar --input ./videos --output ./output --resize_size 256

Bibtex

If you use this code for your research, please consider to star this repo and cite our paper.

@inproceedings{li2021enforcing,
 title={Enforcing Temporal Consistency in Video Depth Estimation},
 author={Li, Siyuan and Luo, Yue and Zhu, Ye and Zhao, Xun and Li, Yu and Shan, Ying},
 booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops},
 year={2021}
}

Acknowledgement

In this project, parts of the code are adapted from: MiDaS. We thank the authors for sharing codes for their great works.

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