Papers with Code 아카이브

2D Semantic Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

17

평가표

11

보존된 평가 기록

42

코드

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

https://github.com/Makunda/DeepLearningASL

Mask R-CNN

https://github.com/MargeryLab/Pytorch-UNet-copy

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/MargeryLab/TransUNet

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

https://github.com/Marior87/Telegram_Bot

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/MartinBuessemeyer/Artistic-Texture-Control

Microsoft COCO: Common Objects in Context

https://github.com/MartinHahner/FoggySynscapes

Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing

https://github.com/MartinHahner88/FoggySynscapes

Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing

https://github.com/Masao-Taketani/FOTS_OCR

FOTS: Fast Oriented Text Spotting with a Unified Network

https://github.com/MasoumehVahedi/Brain_MRI_Segmentation

Attention U-Net: Learning Where to Look for the Pancreas

https://github.com/MatthewQi2002/Unet_mindspore

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/MatusChladek/Semantic-Tissue-Segmentation

TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation

https://github.com/Maveric4/pr19aaw01

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Max-Manning/autoregunsupseg

Autoregressive Unsupervised Image Segmentation

https://github.com/MaybeShewill-CV/CRNN_Tensorflow

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/MaybeShewill-CV/sfnet-tensorflow

Semantic Flow for Fast and Accurate Scene Parsing

https://github.com/Mayurji/Image-Classification-PyTorch

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/MdAli1993/Multiclass_Semantic_Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Media-Smart/vedaseg

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/MegEngine/Models/tree/master/official/vision/segmentation

Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

https://github.com/MehmetBarutcu/PHM-Paper-Implementation

Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters

https://github.com/MenghaoGuo/AutoDeeplab

Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

https://github.com/Mhaiyang/ICCV2019_MirrorNet

Where Is My Mirror?

https://github.com/MiRA-lab-dev/SynRec

FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics

https://github.com/MichalKacprzak99/reconstruction_particle_mass_spectra

Boundary-Seeking Generative Adversarial Networks

https://github.com/MiguelMonteiro/CRFasRNNLayer

Conditional Random Fields as Recurrent Neural Networks

https://github.com/MiguelMonteiro/VNet-Tensorflow

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

https://github.com/Mikoto10032/AutomaticWeightedLoss

Auxiliary Tasks in Multi-task Learning

https://github.com/Miltos-90/UNet_Biomedical_Image_Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Mind23-2/MindCode-101

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/Mind23-2/MindCode-124

DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort

https://github.com/Mind23-2/MindCode-168

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/Mind23-2/MindCode-169

Microsoft COCO: Common Objects in Context

https://github.com/Mind23-2/MindCode-2/tree/main/ViG

ViG-UNet: Vision Graph Neural Networks for Medical Image Segmentation

https://github.com/Mind23-2/MindCode-2/tree/main/vnet

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

https://github.com/Mind23-2/MindCode-26

Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

https://github.com/Mind23-2/MindCode-3

MobileNetV2: Inverted Residuals and Linear Bottlenecks

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