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/anishacharya/Image-Segmentation-FDOG-TRW

On Image segmentation using Fractional Gradients-Learning Model Parameters using Approximate Marginal Inference

https://github.com/anjandeepsahni/face_classification

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/anjandeepsahni/face_recognition

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/ankhoreva/LucidDataDreaming

Lucid Data Dreaming for Video Object Segmentation

https://github.com/ankit-ai/GAN_breast_mammography_segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/ankit-vaghela30/Cilia-Segmentation

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

https://github.com/ankurhanda/SceneNetv1.0

SceneNet: Understanding Real World Indoor Scenes With Synthetic Data

https://github.com/anminhhung/FPT_Hackathon

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/anoushkrit/Knowledge

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/anuragbaurai/Portable-camera-based-assistive-text-reader-for-blind-persons

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

https://github.com/anuragcp/iocl-deepocr

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

https://github.com/anwesanpal/DEDUCE

DEDUCE: Diverse scEne Detection methods in Unseen Challenging Environments

https://github.com/anxingle/UNet-pytorch

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/aod321/Face-parsing-via-tanh-warping

Face Parsing with RoI Tanh-Warping

https://github.com/apacha/OMR-Datasets

DeepScores -- A Dataset for Segmentation, Detection and Classification of Tiny Objects

https://github.com/aparecidovieira/Keras_FusionNet

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

https://github.com/aparecidovieira/Road_extraction

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/apple/ml-neilf

NeILF: Neural Incident Light Field for Physically-based Material Estimation

https://github.com/apple1986/LeViT-UNet

LeViT-UNet: Make Faster Encoders with Transformer for Medical Image Segmentation

https://github.com/aqbewtra/Multi-Class-Aerial-Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/arahusky/Tensorflow-Segmentation

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

https://github.com/archit31uniyal/DC-Gnet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/aris-mukherjee/TransUNet-modified

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

https://github.com/aritzLizoain/Image-segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/arjunakula/neurips2021

CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions

https://github.com/arnab39/equiadapt

Microsoft COCO: Common Objects in Context

https://github.com/arsalhuda24/SS_lstm

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

https://github.com/arthurflor23/surface-crack-detection

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/arvindrajan92/DTrOCR

DTrOCR: Decoder-only Transformer for Optical Character Recognition

https://github.com/aryanasadianuoit/MobileNet_V2

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/aschethor/Spline_PINN

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/aschethor/Unsupervised_Deep_Learning_of_Incompressible_Fluid_Dynamics

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/asgsaeid/ComboLoss

Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentation

https://github.com/ashishpapanai/uNet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/ashokdahal/FrameFieldLearning_Anaconda_Windows

Polygonal Building Segmentation by Frame Field Learning

https://github.com/ashwanirajan/Hurricane-Damage-Detection

Building Damage Annotation on Post-Hurricane Satellite Imagery Based on Convolutional Neural Networks

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