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Back to microsoft/o-cnn

Open-source alternatives to O CNN

16 open-source projects similar to microsoft/o-cnn, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best O CNN alternative.

  • ajbrock/generative-and-discriminative-voxel-modelingajbrock avatar

    ajbrock/Generative-and-Discriminative-Voxel-Modeling

    214View on GitHub↗

    Voxel-Based Variational Autoencoders, VAE GUI, and Convnets for Classification

    Python
    View on GitHub↗214
  • amir32002/feedback-networksamir32002 avatar

    amir32002/feedback-networks

    91View on GitHub↗

    Paper: Feedback Networks, CVPR 2017.

    Lua
    View on GitHub↗91
  • charlesq34/3dcnn.torchcharlesq34 avatar

    charlesq34/3dcnn.torch

    230View on GitHub↗

    Volumetric CNN (Convolutional Neural Networks) for Object Classification on 3D Data, with Torch implementation.

    Lua
    View on GitHub↗230
  • charlesq34/pointnetcharlesq34 avatar

    charlesq34/pointnet

    5,433View on GitHub↗

    PointNet is a deep learning architecture designed to process and classify raw 3D point clouds directly without voxelization. It provides a system for 3D object classification, semantic segmentation frameworks for partitioning clouds into categories, and tools for visualizing 3D shapes. The project utilizes a transform network to align point clouds into a canonical coordinate space and employs symmetric-function-based aggregation to condense point-wise features into global vectors regardless of point order. It also features a multi-scale grouping architecture to extract hierarchical geometric

    Python
    View on GitHub↗5,433
  • charlesq34/pointnet2charlesq34 avatar

    charlesq34/pointnet2

    3,678View on GitHub↗

    PointNet++ is a deep learning framework designed for processing and classifying 3D point cloud data. It utilizes a hierarchical feature learning architecture to extract geometric patterns from sampled 3D point sets. The framework implements a variety of 3D analysis tools, including a point cloud classifier for categorizing objects based on spatial coordinates and surface normals, a semantic scene segmenter for labeling surfaces in large-scale environments, and a tool for 3D object part segmentation. The system covers a broad range of capabilities including geometric feature extraction, 3D da

    Python
    View on GitHub↗3,678

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  • dimatura/voxnetdimatura avatar

    dimatura/voxnet

    386View on GitHub↗

    3D/Volumetric Convolutional Neural Networks with Theano+Lasagne.

    Python
    View on GitHub↗386
  • dylanwusee/pointconvDylanWusee avatar

    DylanWusee/pointconv

    497View on GitHub↗

    PointConv: Deep Convolutional Networks on 3D Point Clouds. CVPR 2019 Wenxuan Wu, Zhongang Qi, Li Fuxin.

    Python
    View on GitHub↗497
  • griegler/octnetgriegler avatar

    griegler/octnet

    504View on GitHub↗

    OctNet uses efficient space partitioning structures (i.e. octrees) to reduce memory and compute requirements of 3D convolutional neural networks, thereby enabling deep learning at high resolutions.

    C++
    View on GitHub↗504
  • itailang/samplenetitailang avatar

    itailang/SampleNet

    392View on GitHub↗

    Created by Itai Lang, Asaf Manor, and Shai Avidan from Tel Aviv University.

    Python
    View on GitHub↗392
  • lmb-freiburg/orionlmb-freiburg avatar

    lmb-freiburg/orion

    129View on GitHub↗

    Here you can find the code for the BMVC 2017 version of "Orientation-boosted Voxel Nets for 3D Object Recognition", a.k.a ORION.

    Matlab
    View on GitHub↗129
  • ranahanocka/meshcnnranahanocka avatar

    ranahanocka/MeshCNN

    1,727View on GitHub↗

    MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used for tasks such as 3D shape classification or segmentation. This framework includes convolution, pooling and unpooling layers which are applied directly on the mesh edges.

    Python
    View on GitHub↗1,727
  • trucleduc/pointgridtrucleduc avatar

    trucleduc/PointGrid

    61View on GitHub↗

    1. Python (with necessary common libraries such as numpy, scipy, etc.) 2. TensorFlow 3. You need to prepare your data in *.mat file with the following format: - 'points': N x 3 array (x, y, z coordinates of the point cloud) - 'labels': N x 1 array (1-based integer per-point labels) - 'category':…

    Python
    View on GitHub↗61
  • xyf513/spidercnnxyf513 avatar

    xyf513/SpiderCNN

    73View on GitHub↗

    SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters. ECCV 2018 Yifan Xu, Tianqi Fan, Mingye Xu, Long Zeng, Yu Qiao.

    Python
    View on GitHub↗73
  • yangyanli/fpnnyangyanli avatar

    yangyanli/FPNN

    55View on GitHub↗

    Field Probing Neural Networks for 3D Data

    C++
    View on GitHub↗55
  • yue-group/meshnetYue-Group avatar

    Yue-Group/MeshNet

    378View on GitHub↗

    Created by Yutong Feng, Yifan Feng, Haoxuan You, Xibin Zhao, Yue Gao from Tsinghua University.

    Python
    View on GitHub↗378
  • zck119/3dgan-releasezck119 avatar

    zck119/3dgan-release

    825View on GitHub↗

    3D Generative Adversarial Network

    Python
    View on GitHub↗825