Papers with Code 아카이브

Semantic Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

29

평가표

150

보존된 평가 기록

1,918

코드

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

https://github.com/2023-MindSpore-4/Code10/tree/main/Efficientnet

EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

https://github.com/2023-MindSpore-4/Code10/tree/main/FCN8s

Fully Convolutional Networks for Semantic Segmentation

https://github.com/2023-MindSpore-4/Code10/tree/main/FCOS

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/2023-MindSpore-4/Code10/tree/main/Inception

InceptionNeXt: When Inception Meets ConvNeXt

https://github.com/2023-MindSpore-4/Code10/tree/main/MaskRCNN

Mask R-CNN

https://github.com/2023-MindSpore-4/Code10/tree/main/OCRNet

Region Rebalance for Long-Tailed Semantic Segmentation

https://github.com/2023-MindSpore-4/Code10/tree/main/PointNet

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

https://github.com/2023-MindSpore-4/Code10/tree/main/PointNet2

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

https://github.com/2023-MindSpore-4/Code10/tree/main/ResNet

Deep Residual Learning for Image Recognition

https://github.com/2023-MindSpore-4/Code10/tree/main/SwinTransformer

Self-Supervised Learning with Swin Transformers

https://github.com/2023-MindSpore-4/Code10/tree/main/Unet

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

https://github.com/2023-MindSpore-4/Code10/tree/main/frustum-pointnet

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/2023-MindSpore-4/Code10/tree/main/glore_res

Graph-Based Global Reasoning Networks

https://github.com/2023-MindSpore-4/Code10/tree/main/hardnet

HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS

https://github.com/2023-MindSpore-4/Code11/tree/main/SPPNet

SPPNet: A Single-Point Prompt Network for Nuclei Image Segmentation

https://github.com/2023-MindSpore-4/Code11/tree/main/Segformer

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

https://github.com/2023-MindSpore-4/Code11/tree/main/SemanticHumanMatting

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

https://github.com/2023-MindSpore-4/Code11/tree/main/SinGAN

SinGAN-Seg: Synthetic training data generation for medical image segmentation

https://github.com/2023-MindSpore-4/Code11/tree/main/resnet50_adv_pruning

Deep Residual Learning for Image Recognition

https://github.com/2023-MindSpore-4/Code11/tree/main/ssc_resnet50

Deep Residual Learning for Image Recognition

https://github.com/2023-MindSpore-4/Code11/tree/main/ssd_resnet_34

Deep Residual Learning for Image Recognition

https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/mae

Masked Autoencoders Are Scalable Vision Learners

https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/sam

Segment Anything

https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/swin

Swin Transformer V2: Scaling Up Capacity and Resolution

https://github.com/2023-MindSpore-4/Code14/tree/main/RepVGG

Make RepVGG Greater Again: A Quantization-aware Approach

https://github.com/2023-MindSpore-4/Code14/tree/main/ResNeSt50

ResNeSt: Split-Attention Networks

https://github.com/2023-MindSpore-4/Code14/tree/main/SPPNet

SPPNet: A Single-Point Prompt Network for Nuclei Image Segmentation

https://github.com/2023-MindSpore-4/Code14/tree/main/Segformer

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

https://github.com/2023-MindSpore-4/Code14/tree/main/SinGAN

SinGAN-Seg: Synthetic training data generation for medical image segmentation

https://github.com/2023-MindSpore-4/Code14/tree/main/res2net

Res2Net: A New Multi-scale Backbone Architecture

https://github.com/2023-MindSpore-4/Code14/tree/main/res2net_deeplabv3

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/2023-MindSpore-4/Code15/tree/main/wangyikai/TokenFusion

Multimodal Token Fusion for Vision Transformers

https://github.com/2023-MindSpore-4/Code2/tree/main/DecoMR

Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes

https://github.com/2023-MindSpore-4/Code3/tree/main/E-NET

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

https://github.com/2023-MindSpore-4/Code3/tree/main/dgcnet_res101

Dual Graph Convolutional Network for Semantic Segmentation

https://github.com/2023-MindSpore-4/Code3/tree/main/dlinknet

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