RGBD_Semantic_Segmentation_PyTorch News Main Results Results on NYU Depth V2 Test Set with Multi-scale Inference Results on CityScapes Test Set with Multi-scale Inference (out method uses output stride=16 and does not use coarse-labeled data) ...
Implement some models of RGB/RGBD semantic segmentation in PyTorch, easy to run. Such as FCN, RefineNet, PSPNet, RDFNet, 3DGNN, PointNet, DeepLab V3, DeepLab V3 plus, DenseASPP, FastFCN - charlesCXK/PyTorch_Semantic_Segmentation
3DGNN for RGB-D segmentation This is the Pytorch implementation of 3D Graph Neural Networks for RGBD Semantic Segmentation: Data Preparation Download NYU_Depth_V2 dataset from here and select scenes and save as ./datasets/data/nyu_depth_v2_labeled.mat Transfer depth images to hha by yourself fr...
3DGNN for RGB-D segmentation This is the Pytorch implementation of3D Graph Neural Networks for RGBD Semantic Segmentation: Data Preparation Download NYU_Depth_V2 dataset fromhereand select scenes and save as./datasets/data/nyu_depth_v2_labeled.mat ...