Official implementation for “MambaDFuse: A Mamba-based Dual-phase Model for Multi-modality Image Fusion.”

DeepLab v3+ model in PyTorch. Support different backbones.

A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.

A Python package to effortlessly assemble images in comparison figures. Supports LaTeX, PPTX, and HTML.

Mamba SSM architecture

U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Pytorch implementation of "LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation"

A collection of loss functions for medical image segmentation

Code release for the TPAMI 2023 paper "Robust Perception and Precise Segmentation for Scribble-Supervised RGB-D Saliency Detection" by Long Li, Junwei Han, Nian Liu*, Salman Khan, Hisham Cholakkal,…

There are four investigated image samples for detecting green algae by our context-sensitive level set model.

[MICCAI 2022] ShapePU: A New PU Learning Framework Regularized by Global Consistency for Scribble Supervised Cardiac Segmentation

ComfyUI custom node that simply integrates the OOTDiffusion.

2.56%, 15.20%, 1.30% on CIFAR10, CIFAR100, and SVHN https://arxiv.org/abs/1708.04552

Official Pytorch implementation of CutMix regularizer

Official PyTorch implementation of "Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup" (ICML'20)

[CVPR 2022] CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision

Scribbles or Points-based weakly-supervised learning for medical image segmentation, a strong baseline, and tutorial for research and application.

An official implementation of "Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation" (CVPR 2021) in PyTorch.

Implementations of recent research prototypes/demonstrations using MONAI.

geodesic distance transform of 2d/3d images

How Distance Transform Maps Boost Segmentation CNNs: An Empirical Study

[MICCAI' 19] NoduleNet: Decoupled False Positive Reduction for Pulmonary Nodule Detection and Segmentation

An open source multi-modality radiation treatment planning sytem developed by e0404 @ DKFZ

🎨 Semantic segmentation models, datasets and losses implemented in PyTorch.

Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/2111.15430

This repository is an unoffical PyTorch implementation of Medical segmentation in 2D and 3D.

We create D3D-HOI a dataset of monocular videos with ground truth annotations of 3D object pose and part motion during human-object interaction.

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

[CVPR 2020] CascadePSP: Toward Class-Agnostic and Very High-Resolution Segmentation via Global and Local Refinement