DIFFNet

This repo is for Self-Supervised Monocular Depth Estimation with Internal Feature Fusion(arXiv), BMVC2021

A new backbone for self-supervised depth estimation.

If you think it is a useful work, please consider citing it.

@inproceedings{zhou_diffnet,
    title={Self-Supervised Monocular Depth Estimation with Internal Feature Fusion},
    author={Zhou, Hang and Greenwood, David and Taylor, Sarah},
    booktitle={British Machine Vision Conference (BMVC)},
    year={2021}
    }

Update:

• [16-05-2022] Adding cityscapes trainining and testing based on Manydepth.

• [22-01-2022] A model diffnet_649x192 uploaded (slightly improved than that of orginal paper)

• [07-12-2021] A multi-gpu training version availible on multi-gpu branch.

Comparing with others

Evaluation on selected hard cases:

Trained weights on KITTI

• Please Note: the results of diffnet_1024x320_ms are not reported in paper *

Setting up before training and testing

• Data preparation: please refer to monodepth2

Training:

sh start2train.sh

Testing:

sh disp_evaluation.sh

Infer a single depth map from a RGB:

sh test_sample.sh

Acknowledgement

Thanks the authors for their works:

• monodepth2
• HRNet