Papers with Code 아카이브

Segmentation

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평가표

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보존된 평가 기록

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코드

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

https://github.com/LUSSeg/ImageNet-S

공식 코드

Large-scale Unsupervised Semantic Segmentation

https://github.com/LZleejean/TexIR_code

공식 코드

Multi-view Inverse Rendering for Large-scale Real-world Indoor Scenes

https://github.com/LanHEU/CTS

공식 코드

CTS: A Consistency-Based Medical Image Segmentation Model

https://github.com/LaoYang1994/SOGNet

공식 코드

SOGNet: Scene Overlap Graph Network for Panoptic Segmentation

https://github.com/Lebourdais/3MAS

공식 코드

Explainable by-design Audio Segmentation through Non-Negative Matrix Factorization and Probing

https://github.com/LeePleased/LeftmostSeg

공식 코드

Neural Sequence Segmentation as Determining the Leftmost Segments

https://github.com/Leedeng/Line-Counter

공식 코드

LineCounter: Learning Handwritten Text Line Segmentation by Counting

https://github.com/LiBingyu01/FGA-seg

공식 코드

FGAseg: Fine-Grained Pixel-Text Alignment for Open-Vocabulary Semantic Segmentation

https://github.com/LiQiufu/3D-WaveUNet

공식 코드

Neuron segmentation using 3D wavelet integrated encoder-decoder network

https://github.com/LiWentomng/BoxInstSeg

공식 코드

Box2Mask: Box-supervised Instance Segmentation via Level-set Evolution

https://github.com/LiheYoung/FreeMask

공식 코드

FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models

https://github.com/Limingxing00/MitoEM2021-Challenge

공식 코드

Advanced Deep Networks for 3D Mitochondria Instance Segmentation

https://github.com/LinZhuoChen/SGNet

공식 코드

Spatial Information Guided Convolution for Real-Time RGBD Semantic Segmentation

https://github.com/Lindsay125/gbpe

공식 코드

Finding Better Subword Segmentation for Neural Machine Translation

https://github.com/LittleWat/multichannel-semseg-with-uda

공식 코드

Multichannel Semantic Segmentation with Unsupervised Domain Adaptation

https://github.com/LiuTingWed/CriDiff

공식 코드

CriDiff: Criss-cross Injection Diffusion Framework via Generative Pre-train for Prostate Segmentation

https://github.com/Lixy1997/Group-WSSS

공식 코드

Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation

https://github.com/LiyaoTang/ERDA

공식 코드

All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation

https://github.com/LongchaoDa/SegmentAsYouWish

공식 코드

Segment as You Wish -- Free-Form Language-Based Segmentation for Medical Images

https://github.com/LucasFidon/GeneralizedWassersteinDiceLoss

공식 코드

Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation using Holistic Convolutional Networks

https://github.com/LucasFidon/HardnessWeightedSampler

공식 코드

Distributionally Robust Deep Learning using Hardness Weighted Sampling

https://github.com/Luffy03/DCA

공식 코드

Deep Covariance Alignment for Domain Adaptive Remote Sensing Image Segmentation

https://github.com/LujianYao/FoSp

공식 코드

FoSp: Focus and Separation Network for Early Smoke Segmentation

https://github.com/Luodian/MADAN

공식 코드

Multi-source Domain Adaptation for Semantic Segmentation

https://github.com/Lydorn/Polygonization-by-Frame-Field-Learning

공식 코드

Polygonal Building Segmentation by Frame Field Learning

https://github.com/MASILab/ALARM

공식 코드

Fully Automatic Liver Attenuation Estimation Combing CNN Segmentation and Morphological Operations

https://github.com/MASILab/SLANTbrainSeg

공식 코드

Spatially Localized Atlas Network Tiles Enables 3D Whole Brain Segmentation from Limited Data

https://github.com/MASILab/SynSeg-Net

공식 코드

SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth

https://github.com/MASILab/coarse_to_fine_prior_seg

공식 코드

RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior

https://github.com/MDL-UzL/DenseSeg

공식 코드

DenseSeg: Joint Learning for Semantic Segmentation and Landmark Detection Using Dense Image-to-Shape Representation

https://github.com/MECLabTUDA/ACS

공식 코드

Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation

https://github.com/MECLabTUDA/Lifelong-nnUNet

공식 코드

Continual Hippocampus Segmentation with Transformers

https://github.com/MECLabTUDA/M3D-NCA

공식 코드

M3D-NCA: Robust 3D Segmentation with Built-in Quality Control

https://github.com/MECLabTUDA/SASVi

공식 코드

SASVi - Segment Any Surgical Video

https://github.com/MIC-DKFZ/MedNeXt

공식 코드

MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation

https://github.com/MIC-DKFZ/Skeleton-Recall

공식 코드

Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures

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