How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Volumetric CNN (Convolutional Neural Networks) for Object Classification on 3D Data, with Torch implementation.
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
Voxel-Based Variational Autoencoders, VAE GUI, and Convnets for Classification
3D/Volumetric Convolutional Neural Networks with Theano+Lasagne.
The main features of dimatura/voxnet are: 3D Object Classification.
Projects with overlapping indexed features include: amir32002/feedback-networks — Paper: Feedback Networks, CVPR 2017. charlesq34/3dcnn.torch — Volumetric CNN (Convolutional Neural Networks) for Object Classification on 3D Data, with Torch implementation. charlesq34/pointnet — PointNet is a deep learning architecture designed to process and classify raw 3D point clouds directly without… charlesq34/pointnet2 — PointNet++ is a deep learning framework designed for processing and classifying 3D point cloud data. It utilizes a… dylanwusee/pointconv — PointConv: Deep Convolutional Networks on 3D Point Clouds. CVPR 2019 Wenxuan Wu, Zhongang Qi, Li Fuxin. ajbrock/generative-and-discriminative-voxel-modeling — Voxel-Based Variational Autoencoders, VAE GUI, and Convnets for Classification.
