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This is the Pytorch implementation of [3D Graph Neural Networks for RGBD Semantic Segmentation](http://openaccess.thecvf.com/content_ICCV_2017/papers/Qi_3D_Graph_Neural_ICCV_2017_paper.pdf):
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### Data Preparation
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1. Download NYU_Depth_V2 dataset from [here](https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html) and save as `./datasets/data/nyu_depth_v2_labeled.mat`
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1. Download NYU_Depth_V2 dataset from [here](https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html) and select scenes and save as `./datasets/data/nyu_depth_v2_labeled.mat`
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2. Transfer depth images to hha by yourself from [here](https://github.com/charlesCXK/Depth2HHA) and save in `./datasets/data/hha/`.
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