Depth-aware CNN for RGB-D Segmentation [Arxiv]
Install Pytorch, dominate, TensorBoardX.
The depth-aware convolution and depth-aware average pooling operations are under folder models/ops, to build them, simply use sh make.sh to compile.
#!./scripts/train.sh
python train.py \
--name nyuv2_VGGdeeplab_depthconv \
--dataset_mode nyuv2 \
--flip --scale --crop --colorjitter \
--depthconv \
--list dataset/lists/nyuv2/train.lst \
--vallist dataset/lists/nyuv2/val.lst#!./scripts/test.sh
python test.py \
--name nyuv2_VGGdeeplab_depthconv \
--dataset_mode nyuv2 \
--list dataset/lists/nyuv2/test.lst \
--depthconv \
--how_many 0If you find this work useful, please consider citing:
@inproceedings{wang2018depthconv,
title={Depth-aware CNN for RGB-D Segmentation},
author={Wang, Weiyue and Neumann, Ulrich},
booktitle={ECCV},
year={2018}
}
The visulization code is borrowed from pytorch-CycleGAN-and-pix2pix. Here is a pytorch implementation of DeepLab.
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