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/YudeWang/UNet-Satellite-Image-Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Yuting-Gao/CRNN_Mxnet

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

https://github.com/YuzheZhang-1999/DiffTSR

Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions

https://github.com/ZE-WEN/DendriteSAM

Segment Anything

https://github.com/ZFTurbo/ZF_UNET_224_Pretrained_Model

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/ZFTurbo/segmentation_models_3D

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/ZQPei/deep_sort_pytorch

Mask R-CNN

https://github.com/ZXdatascience/TextDetectorAndroid

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/ZZWENG/holistic_mesh

Holistic 3D Human and Scene Mesh Estimation from Single View Images

https://github.com/Zahra2351373/Image-Processing-Final-Project

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Zakobian/CT_framework_

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/ZeeTsing/Carvana_challenge

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Zhanghongbin-github/SegNet-Tutorial

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

https://github.com/ZhecanJamesWang/GLAT_SGG

Knowledge-Embedded Routing Network for Scene Graph Generation

https://github.com/ZhecanJamesWang/GLAT_Visual_Commonsense

Learning Visual Commonsense for Robust Scene Graph Generation

https://github.com/ZhenboSong/RobustSIRR

https://github.com/Zhz1997/Singing-voice-speration-with-U-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/a-martyn/unet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/aalmah/augmented_cyclegan

Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data

https://github.com/aayushmanace/patchalign24

Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation

https://github.com/ababier/open-kbp

Enhancing Organ at Risk Segmentation with Improved Deep Neural Networks

https://github.com/abdallahyamie/python-master

Open-World Entity Segmentation

https://github.com/abdulwaheedsoudagar/ImageTextTranslation

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

https://github.com/abhi1kumar/M3D-RPN

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/abhi4ssj/squeeze_and_excitation

Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks

https://github.com/abhigoyal1997/CS-763-Project

Exploring Models and Data for Image Question Answering

https://github.com/abhijain864/Project_2020_May-July

Adapting Deep Network Features to Capture Psychological Representations

https://github.com/abhijain864/Project_Comparing_neural-nets-with-pyschological-representations-

Adapting Deep Network Features to Capture Psychological Representations

https://github.com/abhijain864/Summer_Project_2020

Adapting Deep Network Features to Capture Psychological Representations

https://github.com/abhiraman/Capstone_Project

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

https://github.com/abhishekaich27/proscale-pytorch

Efficient Transformer Encoders for Mask2Former-style models

https://github.com/abugler/SMLFinalProject

Deep clustering: Discriminative embeddings for segmentation and separation

https://github.com/acaelles97/devis

Make One-Shot Video Object Segmentation Efficient Again

https://github.com/acasamitjana/jump

Robust Segmentation of Brain MRI in the Wild with Hierarchical CNNs and no Retraining

https://github.com/achalddave/segment-any-moving

Towards Segmenting Anything That Moves

https://github.com/achen353/face-mask-detector

MobileNetV2: Inverted Residuals and Linear Bottlenecks

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