There are 15 repositories under 3d-segmentation topic.
3D U-Net model for volumetric semantic segmentation written in pytorch
🔥[IEEE TPAMI 2020] Deep Learning for 3D Point Clouds: A Survey
🔥PCL(Point Cloud Library)点云库学习记录
Segment Anything in 3D with NeRFs (NeurIPS 2023)
The official implementation of SAGA (Segment Any 3D GAussians)
RELLIS-3D: A Multi-modal Dataset for Off-Road Robotics
🔥DM-NeRF in PyTorch (ICLR 2023)
Brainchop: In-browser 3D MRI rendering and segmentation
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet and has the capability to segment 120 unique tissue classes from a whole-body 18F-FDG PET/CT image.
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.
[WACV 2024] Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation
点云分割论文2017 Fast segmentation of 3d point clouds: A paradigm on lidar data for autonomous vehicle applications
3D点云语义分割汇总,所有顶会论文以及一些arxiv上的最新论文
基于Qt实现的图片数据标注工具. Image Annotation Tool Based on Qt, supporting 2D/3D Detection/Segmentation Annotation.
The implementation of 3D-UNet using PyTorch
TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes
Repository for the paper "Extending Maps with Semantic and Contextual Object Information for Robot Navigation: a Learning-Based Framework using Visual and Depth Cues"
3D augmentation and transforms of 2D/3D sparse data, such as 3D triangle meshes or point clouds in Euclidean space. Extension of the Fast.ai library to train Sub-manifold Sparse Convolution Networks
Utils and convenience functions for large-scale bio-image analysis.
VNet for 3d volume segmentation
Paper list of deep learning on point clouds.
This is the official repository of the original Point Transformer architecture.
Distributed segmentation for bio-image-analysis
LiDARNet: A Boundary-Aware Domain Adaptation Model for Point Cloud Semantic Segmentation
A Tensorflow Implementation of Brain Tumor Segmentation using Topological Loss
This is the official repo for Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation (ICCV 23).
3D medical image semantic segmentation with Pytorch.
Brain tumors segmentation on 3D MRI images. The model has been trained on BratTS20 and BraTS21 datasets, and now working with BraTS23.