Segment Anything in 3D with NeRFs (NeurIPS 2023)
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Updated
Apr 16, 2024 - Python
Segment Anything in 3D with NeRFs (NeurIPS 2023)
[ICCV2023] Official Implementation of "UniTR: A Unified and Efficient Multi-Modal Transformer for Bird’s-Eye-View Representation"
🔥DM-NeRF in PyTorch (ICLR 2023)
[CVPR 2021] Few-shot 3D Point Cloud Semantic 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.
[WACV 2024] Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image 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.
This is the official implementation of RSNet.
Set of models for segmentation of 3D volumes
The implementation of 3D-UNet using PyTorch
Repository for the paper "Extending Maps with Semantic and Contextual Object Information for Robot Navigation: a Learning-Based Framework using Visual and Depth Cues"
[ICLR 2024] AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation
Softmax for Arbitrary Label Trees (SALT) is a framework for training segmentation networks using conditional probabilities to model hierarchical relationships in the data.
Utils and convenience functions for large-scale bio-image analysis.
VNet for 3d volume segmentation
This is the official repository of the original Point Transformer architecture.
Distributed segmentation for bio-image-analysis
A Tensorflow Implementation of Brain Tumor Segmentation using Topological Loss
Brain tumors segmentation on 3D MRI images. The model has been trained on BratTS20 and BraTS21 datasets, and now working with BraTS23.
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