Papers with Code 아카이브

Segmentation

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/horsepurve/StyleSegor

공식 코드

Neural Style Transfer Improves 3D Cardiovascular MR Image Segmentation on Inconsistent Data

https://github.com/hossein1387/U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation

공식 코드

U-Net Fixed-Point Quantization for Medical Image Segmentation

https://github.com/hritam-98/MFSNet

공식 코드

MFSNet: A Multi Focus Segmentation Network for Skin Lesion Segmentation

https://github.com/hritam-98/gfda-disentangled

공식 코드

Semi-supervised Domain Adaptive Medical Image Segmentation through Consistency Regularized Disentangled Contrastive Learning

https://github.com/hritam-98/ict-medseg

공식 코드

An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation

https://github.com/hrlblab/IRS

공식 코드

IRS: Incremental Relationship-guided Segmentation for Digital Pathology

https://github.com/hrlblab/glo-in-one_v2

공식 코드

Glo-In-One-v2: Holistic Identification of Glomerular Cells, Tissues, and Lesions in Human and Mouse Histopathology

https://github.com/hrlblab/hats

공식 코드

HATs: Hierarchical Adaptive Taxonomy Segmentation for Panoramic Pathology Image Analysis

https://github.com/hrlblab/molecularel

공식 코드

Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning

https://github.com/hrzhang1123/cvm_ws_segmentation

공식 코드

Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational model

https://github.com/hsiangyuzhao/PANet

공식 코드

Prior Attention Network for Multi-Lesion Segmentation in Medical Images

https://github.com/hsiangyuzhao/adler

공식 코드

AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation

https://github.com/hsiangyuzhao/rcps

공식 코드

RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation

https://github.com/hsp-iit/online-detection

공식 코드

Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub Robot

https://github.com/hszhao/ICNet

공식 코드

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

https://github.com/hu64/SpotNet

공식 코드

SpotNet: Self-Attention Multi-Task Network for Object Detection

https://github.com/huaaaliu/rgbx_semantic_segmentation

공식 코드

CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers

https://github.com/huaibei-normal-university-cv-laboratory/mbdresunet

공식 코드

MBDRes-U-Net: Multi-Scale Lightweight Brain Tumor Segmentation Network

https://github.com/huangdlab/enformer

공식 코드

Ensemble architecture in polyp segmentation

https://github.com/huangjh-pub/multibody-sync

공식 코드

MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization

https://github.com/huanglizi/c2fvl

공식 코드

Coarse-to-Fine Covid-19 Segmentation via Vision-Language Alignment

https://github.com/huanglizi/lvit

공식 코드

LViT: Language meets Vision Transformer in Medical Image Segmentation

https://github.com/huanglizi/scribblevc

공식 코드

ScribbleVC: Scribble-supervised Medical Image Segmentation with Vision-Class Embedding

https://github.com/huanglizi/stpnet

공식 코드

STPNet: Scale-aware Text Prompt Network for Medical Image Segmentation

https://github.com/huangmozhilv/u2net_torch

공식 코드

3D U$^2$-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation

https://github.com/huangshiqi128/zori

공식 코드

ZoRI: Towards Discriminative Zero-Shot Remote Sensing Instance Segmentation

https://github.com/huangyjhust/3D-RU-Net

공식 코드

3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation

https://github.com/huaqinghe/joined

공식 코드

JOINED : Prior Guided Multi-task Learning for Joint Optic Disc/Cup Segmentation and Fovea Detection

https://github.com/hugo-oliveira/CoDAGANs

공식 코드

Truly Generalizable Radiograph Segmentation with Conditional Domain Adaptation

https://github.com/hugo-oliveira/fsws_metalearning

공식 코드

Meta-Learners for Few-Shot Weakly-Supervised Medical Image Segmentation

https://github.com/hugo-oliveira/openseg

공식 코드

Fully Convolutional Open Set Segmentation

https://github.com/huiimin5/aua

공식 코드

Exploring Feature Representation Learning for Semi-supervised Medical Image Segmentation

https://github.com/huiimin5/comwin

공식 코드

Compete to Win: Enhancing Pseudo Labels for Barely-supervised Medical Image Segmentation

https://github.com/huiqianli/asps

공식 코드

ASPS: Augmented Segment Anything Model for Polyp Segmentation

https://github.com/huiserwang/ContrastMask

공식 코드

ContrastMask: Contrastive Learning to Segment Every Thing

https://github.com/huixiancheng/PCB-RandNet

공식 코드

PCB-RandNet: Rethinking Random Sampling for LIDAR Semantic Segmentation in Autonomous Driving Scene

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