Papers with Code 아카이브

Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

5

보존된 평가 기록

6

코드

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

https://github.com/sora763/uncertainty

공식 코드

Improving the Reliability of Semantic Segmentation of Medical Images by Uncertainty Modeling with Bayesian Deep Networks and Curriculum Learning

https://github.com/sosppxo/3d-stmn

공식 코드

3D-STMN: Dependency-Driven Superpoint-Text Matching Network for End-to-End 3D Referring Expression Segmentation

https://github.com/sosppxo/MDIN

공식 코드

3D-GRES: Generalized 3D Referring Expression Segmentation

https://github.com/sosppxo/rg-san

공식 코드

RG-SAN: Rule-Guided Spatial Awareness Network for End-to-End 3D Referring Expression Segmentation

https://github.com/sotiraslab/AgileFormer

공식 코드

AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation

https://github.com/sotiraslab/QCResUNet

공식 코드

QCResUNet: Joint Subject-level and Voxel-level Segmentation Quality Prediction

https://github.com/sotiraslab/dlk

공식 코드

D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image Segmentation

https://github.com/sotiraslab/dynamicunet

공식 코드

Dynamic U-Net: Adaptively Calibrate Features for Abdominal Multi-organ Segmentation

https://github.com/soumbane/dualselfdistillation

공식 코드

Volumetric medical image segmentation through dual self-distillation in U-shaped networks

https://github.com/soumickmj/GPModels

공식 코드

Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification

https://github.com/soumickmj/pulaski

공식 코드

PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation

https://github.com/soumickmj/spockmip

공식 코드

SPOCKMIP: Segmentation of Vessels in MRAs with Enhanced Continuity using Maximum Intensity Projection as Loss

https://github.com/soumickmj/turbolift

공식 코드

Liver Segmentation using Turbolift Learning for CT and Cone-beam C-arm Perfusion Imaging

https://github.com/soumyaxyz/abstractAnalysis

공식 코드

Segmenting Scientific Abstracts into Discourse Categories: A Deep Learning-Based Approach for Sparse Labeled Data

https://github.com/speedinghzl/AlignSeg

공식 코드

AlignSeg: Feature-Aligned Segmentation Networks

https://github.com/speedinghzl/CCNet

공식 코드

CCNet: Criss-Cross Attention for Semantic Segmentation

https://github.com/splinterli/sattca

공식 코드

Scale-aware Test-time Click Adaptation for Pulmonary Nodule and Mass Segmentation

https://github.com/spyflying/CMPC-Refseg

공식 코드

Cross-Modal Progressive Comprehension for Referring Segmentation

https://github.com/sqbqamar/SAMA-UNet

공식 코드

SAMA-UNet: Enhancing Medical Image Segmentation with Self-Adaptive Mamba-Like Attention and Causal-Resonance Learning

https://github.com/sqbqamar/scalefusionnet

공식 코드

ScaleFusionNet: Transformer-Guided Multi-Scale Feature Fusion for Skin Lesion Segmentation

https://github.com/sqhuang0103/samreg

공식 코드

SAMReg: SAM-enabled Image Registration with ROI-based Correspondence

https://github.com/sr0920/cit-net

공식 코드

CiT-Net: Convolutional Neural Networks Hand in Hand with Vision Transformers for Medical Image Segmentation

https://github.com/sr0920/tec-net

공식 코드

TEC-Net: Vision Transformer Embrace Convolutional Neural Networks for Medical Image Segmentation

https://github.com/srv/Posidonia-semantic-segmentation

공식 코드

Deep Semantic Segmentation in an AUV for Online Posidonia Oceanica Meadows identification

https://github.com/ssarfraz/FINCH-CLustering

공식 코드

Temporally-Weighted Hierarchical Clustering for Unsupervised Action Segmentation

https://github.com/ssssshwan/tldr

공식 코드

Texture Learning Domain Randomization for Domain Generalized Segmentation

https://github.com/sstary/ssrs

공식 코드

SAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary Constraints

https://github.com/ssyc123/siseg

공식 코드

Synthetic Instance Segmentation from Semantic Image Segmentation Masks

https://github.com/ssyc123/tfiseg

공식 코드

Synthetic Instance Segmentation from Semantic Image Segmentation Masks

https://github.com/stanfordmlgroup/CheXseg

공식 코드

CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation

https://github.com/stanley-313/imagesegfm-survey

공식 코드

Image Segmentation in Foundation Model Era: A Survey

https://github.com/starbucks-drinker/mi-segnet

공식 코드

MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain Generalization

https://github.com/stardist/stardist

공식 코드

Cell Detection with Star-convex Polygons

https://github.com/statmlben/rankseg

공식 코드

RankSEG: A Consistent Ranking-based Framework for Segmentation

https://github.com/stefan-ainetter/grasp_det_seg_cnn

공식 코드

End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB

https://github.com/steff-farley/AFM-image-segmentation

공식 코드

Improving the Segmentation of Scanning Probe Microscope Images using Convolutional Neural Networks

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