PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
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Updated
May 7, 2020 - Python
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PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
Pytorch framework for doing deep learning on point clouds.
Grid-GCN for Fast and Scalable Point Cloud Learning
4D Spatio-Temporal Semantic Segmentation on a 3D video (a sequence of 3D scans)
FPConv: Learning Local Flattening for Point Convolution, CVPR 2020
FrameNet: Learning Local Canonical Frames of 3D Surfaces from a Single RGB Image
TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes
This work is based on our paper "DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes", which appeared at the IEEE Conference On Computer Vision And Pattern Recognition (CVPR) 2020.
ENet for 2D semantic segmentation in ScanNet
PFA-ScanNet: Pyramidal Feature Aggregation with Synergistic Learning for Breast Cancer Metastasis Analysis
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