3D U-Net model for volumetric semantic segmentation written in pytorch
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Updated
Jul 30, 2024 - Jupyter Notebook
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)
Brainchop: In-browser 3D MRI rendering and segmentation
RELLIS-3D: A Multi-modal Dataset for Off-Road Robotics
[ICCV2023] Official Implementation of "UniTR: A Unified and Efficient Multi-Modal Transformer for Bird’s-Eye-View Representation"
🔥DM-NeRF in PyTorch (ICLR 2023)
[WACV 2024] Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image 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.
[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation
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.
Set of models for segmentation of 3D volumes
This is the official implementation of RSNet.
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
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