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/barahona-research-group/severability

Severability of mesoscale components and local time scales in dynamical networks

https://github.com/bcmi/graconet-object-placement

Context-Aware Synthesis and Placement of Object Instances

https://github.com/bcmi/madisnet-inharmonious-region-localization

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/bcmi/phdnet-painterly-image-harmonization

Microsoft COCO: Common Objects in Context

https://github.com/bcv-uniandes/job-vs

Towards Robust General Medical Image Segmentation

https://github.com/beassssry/U

Mask R-CNN

https://github.com/benolmbrt/MedicOOD

Improving Calibration and Out-of-Distribution Detection in Medical Image Segmentation with Convolutional Neural Networks

https://github.com/berenslab/retinal-vessel-segmentation-benchmark

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/bestaar/predictiveFilterFlow

Multigrid Predictive Filter Flow for Unsupervised Learning on Videos

https://github.com/bethgelab/siamese-mask-rcnn

Mask R-CNN

https://github.com/bfortuner/pytorch_tiramisu

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/bgshih/aster

https://github.com/bgshih/crnn

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

https://github.com/bharaniabhishek123/cs231n_project

Gleason Grading of Histology Prostate Images through Semantic Segmentation via Residual U-Net

https://github.com/bharath3794/UNet-Image-Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/bharatsush/TextSpotting

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

https://github.com/bhavitvyamalik/OCR-using-CRNN

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

https://github.com/bhavyagoyal/spclowlight

Photon-Starved Scene Inference using Single Photon Cameras

https://github.com/bhumigodiwala/Face-Mask-Detection

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/bigmb/Unet-Segmentation-Pytorch-Nest-of-Unets

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/billlyzhaoyh/SegNetFromScratch

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/birdman9390/MetaMaskTrack

Learning Video Object Segmentation from Static Images

https://github.com/biss/unet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/black0017/MedicalZooPytorch

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

https://github.com/blaze1522/Image-Segmentation-FloodNet

FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding

https://github.com/blumenstiel/CAT-Seg-MESS

CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation

https://github.com/bo-10000/VoxResNet

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

https://github.com/bonlime/keras-deeplab-v3-plus

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/boom85423/Cartoon-style-Stickers-Generator

Mask R-CNN

https://github.com/boris127/vehicle-detection

The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation

https://github.com/bowang-lab/shape-attentive-unet

SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation

https://github.com/bowen-upenn/Multi-Agent-VQA

Less is More: Toward Zero-Shot Local Scene Graph Generation via Foundation Models

https://github.com/bowu1004/instance_segmentation_RealSense

Mask R-CNN

https://github.com/bragancas/vnet_pytorch-atriaseg2018

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/branislavhesko/segmentation_framework

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/brdiep113/UNet

U-Net: Convolutional Networks for Biomedical Image Segmentation

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