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/2023-MindSpore-4/Code8/tree/main/cnnctc

What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis

https://github.com/2023-MindSpore-4/Code9/tree/main/MaskRCNN

Mask R-CNN

https://github.com/2023-MindSpore-4/Code9/tree/main/OCRNet

Distilling Ensemble of Explanations for Weakly-Supervised Pre-Training of Image Segmentation Models

https://github.com/2023-MindSpore-4/Code9/tree/main/Unet

Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras

https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/clipseg

Image Segmentation Using Text and Image Prompts

https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/groupvit

GroupViT: Semantic Segmentation Emerges from Text Supervision

https://github.com/2024-MindSpore-1/Code3/tree/main/VisionLAN

From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network

https://github.com/2024-MindSpore-1/Code4/tree/main/DeepLabV3P

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

https://github.com/2024-MindSpore-1/Code4/tree/main/DeepLabv3

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/2024-MindSpore-1/Code4/tree/main/MobileNet/mobilenetv2

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/2024-MindSpore-1/Code6/tree/main/Auto-DeepLab

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

https://github.com/2024-MindSpore-1/Code6/tree/main/augvit

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

https://github.com/2024-MindSpore-1/Code7/tree/main/cnn_direction_model

Structured Sparse R-CNN for Direct Scene Graph Generation

https://github.com/2024-MindSpore-1/Code7/tree/main/cnnctc

What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis

https://github.com/2024-MindSpore-1/Code7/tree/main/convmixer

CMU-Net: A Strong ConvMixer-based Medical Ultrasound Image Segmentation Network

https://github.com/2manslkh/korean-food-classification-flask

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/3P2S/arcface

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/44aayush/Denoising-and-Enhancement

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/4uiiurz1/pytorch-nested-unet

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

https://github.com/9p15p/frtm-vos

Learning Fast and Robust Target Models for Video Object Segmentation

https://github.com/9ruddls3/CRNN_Pytorch

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

https://github.com/AD2605/Action-Recognition

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/AICIP-UTK/spacenet-round3

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/AIwithSwift/TFWorld2019-SwiftIn3Hours

Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions

https://github.com/AKASH2907/bird-species-classification

Mask R-CNN

https://github.com/AKASH2907/bird_species_classification

Mask R-CNN

https://github.com/Abe404/segmentation_of_roots_in_soil_with_unet

Segmentation of Roots in Soil with U-Net

https://github.com/Adarol/u-net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Adityarajora/qwerty

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Aggrawal5497/UNet-Image-segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Akelyaporten/DC-UNet

DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentation

https://github.com/Akhilesh64/ResUnet-a

ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data

https://github.com/AleksBanbur/EE8204---Real-Time-Multi-Task-Learning

Light-Weight RefineNet for Real-Time Semantic Segmentation

https://github.com/Alexander-Whelan/Zeus

Mask R-CNN

https://github.com/AlexandreBrown/AerialSemanticSegmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Alihussain1/Image-Segmentation

A Novel Approach for Image Segmentation based on Histograms computed from Hue-data

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