Papers with Code 아카이브

Segmentation

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평가표

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보존된 평가 기록

6

코드

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

https://github.com/HiLab-git/ACELoss

공식 코드

Learning Euler's Elastica Model for Medical Image Segmentation

https://github.com/HiLab-git/CA-Net

공식 코드

CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation

https://github.com/HiLab-git/DTC

공식 코드

Semi-supervised Medical Image Segmentation through Dual-task Consistency

https://github.com/HiLab-git/Head-Neck-GTV

공식 코드

Automatic Segmentation of Gross Target Volume of Nasopharynx Cancer using Ensemble of Multiscale Deep Neural Networks with Spatial Attention

https://github.com/HiLab-git/SSL4MIS

공식 코드

Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency

https://github.com/HiLab-git/SepNet

공식 코드

Automatic Segmentation of Organs-at-Risk from Head-and-Neck CT using Separable Convolutional Neural Network with Hard-Region-Weighted Loss

https://github.com/HiLab-git/UGIR

공식 코드

Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices

https://github.com/HiLab-git/WSL4MIS

공식 코드

Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision

https://github.com/Hippogriff/prifit

공식 코드

PriFit: Learning to Fit Primitives Improves Few Shot Point Cloud Segmentation

https://github.com/Hk416mod2/OVS-Net

공식 코드

Optimized Vessel Segmentation: A Structure-Agnostic Approach with Small Vessel Enhancement and Morphological Correction

https://github.com/HoangTrinh/EDMS

공식 코드

Image Compression with Encoder-Decoder Matched Semantic Segmentation

https://github.com/Holliemin9090/Mammographic-mass-CAD-via-pseudo-color-mammogram-and-Mask-R-CNN

공식 코드

Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN

https://github.com/HolmesShuan/Location-aware-Upsampling-for-Semantic-Segmentation

공식 코드

Location-aware Upsampling for Semantic Segmentation

https://github.com/HuXiaoling/TopoLoss

공식 코드

Topology-Preserving Deep Image Segmentation

https://github.com/HuaiChen-1994/LDLearning

공식 코드

Unsupervised Local Discrimination for Medical Images

https://github.com/HzFu/AGNet

공식 코드

Attention Guided Network for Retinal Image Segmentation

https://github.com/HzFu/COVID19_imaging_AI_paper_list

공식 코드

Towards Data-Efficient Learning: A Benchmark for COVID-19 CT Lung and Infection Segmentation

https://github.com/IBBM/Cascaded-FCN

공식 코드

Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields

https://github.com/ICT-MIRACLE-lab/CTSpine1K

공식 코드

CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

https://github.com/IDEA-Research/Grounded-Segment-Anything

공식 코드

Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

https://github.com/INZHAGY/WDA-Net

공식 코드

WDA-Net: Weakly-Supervised Domain Adaptive Segmentation of Electron Microscopy

https://github.com/IPMI-ICNS-UKE/NFSegmentationPipeline

공식 코드

Anatomy-Informed Deep Learning and Radiomics for Automated Neurofibroma Segmentation in Whole-Body MRI

https://github.com/IRVLUTD/FewSOL-DataLoader

공식 코드

FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments

https://github.com/IRVLUTD/fewsol-toolkit

공식 코드

FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments

https://github.com/IRVLUTD/meta-dataset

공식 코드

FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments

https://github.com/IkeaASM/IKEA_ASM_Dataset

공식 코드

The IKEA ASM Dataset: Understanding People Assembling Furniture through Actions, Objects and Pose

https://github.com/Ilya-Fradlin/Interactive4D

공식 코드

Interactive4D: Interactive 4D LiDAR Segmentation

https://github.com/Inha-CVAI/MADGNet

공식 코드

Modality-agnostic Domain Generalizable Medical Image Segmentation by Multi-Frequency in Multi-Scale Attention

https://github.com/InnovArul/vidreid_cosegmentation

공식 코드

Co-segmentation Inspired Attention Module for Video-based Computer Vision Tasks

https://github.com/IntuitionMachines/OrigamiNet

공식 코드

OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold

https://github.com/IonutMotoi/CutPasteSatSeg

공식 코드

Evaluating the Efficacy of Cut-and-Paste Data Augmentation in Semantic Segmentation for Satellite Imagery

https://github.com/IssamLaradji/CBStyling

공식 코드

Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation

https://github.com/IssamLaradji/affinity_lcfcn

공식 코드

Affinity LCFCN: Learning to Segment Fish with Weak Supervision

https://github.com/IvanEz/Red-GAN

공식 코드

Red-GAN: Attacking class imbalance via conditioned generation. Yet another perspective on medical image synthesis for skin lesion dermoscopy and brain tumor MRI

https://github.com/JG-codies/MicroAnalyzer

공식 코드

MicroAnalyzer: A Python Tool for Automated Bacterial Analysis with Fluorescence Microscopy

https://github.com/JJGO/UniverSeg

공식 코드

UniverSeg: Universal Medical Image Segmentation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.