TCMonoDepth
TCMonoDepth copied to clipboard
Enforcing Temporal Consistency in Video Depth Estimation, ICCV-W 2021.
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。
Usage
Requirements
- [x] python
- [x] pytorch
- [x] torchvision
- [x] opencv
- [x] 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.