Papers with Code 아카이브

2D Semantic Segmentation

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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/SRDAMICCAI/Source-Relaxed-Domain-Adaptation

Source-Relaxed Domain Adaptation for Image Segmentation

https://github.com/SSN15/Behavioral-Cloning--Implementaion-of-Autonomous-car-using-deep-learning

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

https://github.com/SUYEgit/Surgery-Robot-Detection-Segmentation

Mask R-CNN

https://github.com/SWKoreaBME/D-Unet_PyTorch

D-UNet: a dimension-fusion U shape network for chronic stroke lesion segmentation

https://github.com/SYR-Aegis/BrailleOCR

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

https://github.com/SahinTiryaki/Brain-tumor-segmentation-Vgg19UNet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/SaifeddineBarkia/Multi-view-radar-semantic-segmentation-for-scene-understanding-in-autonomous-driving

Multi-View Radar Semantic Segmentation

https://github.com/Sakib1263/MobileNet-1D-2D-Tensorflow-Keras

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/SamvitJ/Accel

Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video

https://github.com/Saritus/Crowd-Counter

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

https://github.com/SarthakGarg13/Severstal-Steel-Defect-Detection

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Scalsol/mega.pytorch

Deep Feature Flow for Video Recognition

https://github.com/Scienceseb/Learning-of-Image-Dehazing-Models-for-Segmentation-Tasks

Learning of Image Dehazing Models for Segmentation Tasks

https://github.com/SenthilCaesar/CNN-Brain-MRI-Segmentation

CompNet: Complementary Segmentation Network for Brain MRI Extraction

https://github.com/Sentient07/HeadHunter-T

Tracking Pedestrian Heads in Dense Crowd

https://github.com/SeonbeomKim/TensorFlow-pix2pix

U-Net: Convolutional Networks for Biomedical Image Segmentation

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

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

https://github.com/SeyedMuhammadHosseinMousavi/Neural-Gas-Network-Image-Features-and-Segmentation-for-Brain-Tumor-Detection-Using-MRI-Data

Neural Gas Network Image Features and Segmentation for Brain Tumor Detection Using Magnetic Resonance Imaging Data

https://github.com/SfTI-Robotics/ROS-label-node

Mask R-CNN

https://github.com/ShahedSabab/imagePrep

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/ShaileshKumar97/Speech-Enhancement

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/SharadGitHub/OctaveUnet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Sharut/CT_Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/ShawFromAttock/FYP-Medical-Image-Segmentation-using-Nested-UNet-Architecture

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

https://github.com/ShichengChen/WaveUNet

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

https://github.com/ShuaiChenBIGR/MASSL-segmentation-framework

Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation

https://github.com/Shualite/SFNet.pytorch

Semantic Flow for Fast and Accurate Scene Parsing

https://github.com/Shumway82/U-Net-Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Shun14/UperNet

Unified Perceptual Parsing for Scene Understanding

https://github.com/Shun14/deeplab-paddle

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

https://github.com/ShunyuYao/blitznet_instance_segment

BlitzNet: A Real-Time Deep Network for Scene Understanding

https://github.com/SilvioGiancola/SoccerNetv2-DevKit

SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos

https://github.com/Simurgh818/UCSF_QBI_Hackathon_ImageSegmentor

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/SixQuant/U-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/SkyWa7ch3r/ImageSegmentation

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

https://github.com/SkyWa7ch3r/SceneSegmentation

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

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