SOTAVerified

Image Segmentation

Image Segmentation is a computer vision task that involves dividing an image into multiple segments or regions, each of which corresponds to a different object or part of an object. The goal of image segmentation is to assign a unique label or category to each pixel in the image, so that pixels with similar attributes are grouped together.

Papers

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Showing 3651–3700 of 5035 papers

TitleStatusHype
Cross-Modal Self-Attention Distillation for Prostate Cancer Segmentation—0
Cross-model Mutual Learning for Exemplar-based Medical Image Segmentation—0
Cross-Organ Domain Adaptive Neural Network for Pancreatic Endoscopic Ultrasound Image Segmentation—0
Cross Pixel Optical Flow Similarity for Self-Supervised Learning—0
Few-shot Medical Image Segmentation via Cross-Reference Transformer—0
Cross-supervised Dual Classifiers for Semi-supervised Medical Image Segmentation—0
Crowd Sourcing Image Segmentation with iaSTAPLE—0
CT Image Segmentation for Inflamed and Fibrotic Lungs Using a Multi-Resolution Convolutional Neural Network—0
CT Image Synthesis Using Weakly Supervised Segmentation and Geometric Inter-Label Relations For COVID Image Analysis—0
CTI-Unet: Cascaded Threshold Integration for Improved U-Net Segmentation of Pathology Images—0
CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss—0
CT Synthesis with Conditional Diffusion Models for Abdominal Lymph Node Segmentation—0
CUAB: Convolutional Uncertainty Attention Block Enhanced the Chest X-ray Image Analysis—0
Cubic Spline Interpolation Segmenting over Conventional Segmentation Procedures: Application and Advantages—0
Curriculum Point Prompting for Weakly-Supervised Referring Image Segmentation—0
Curve-Structure Segmentation from Depth Maps: A CNN-based Approach and Its Application to Exploring Cultural Heritage Objects—0
Customizable Architecture Search for Semantic Segmentation—0
Customized SAM 2 for Referring Remote Sensing Image Segmentation—0
Task-Specific Adaptation of Segmentation Foundation Model via Prompt Learning—0
CUSUM Filter for Brain Segmentation on DSC Perfusion MR Head Scans with Abnormal Brain Anatomy—0
Cut, Glue & Cut: A Fast, Approximate Solver for Multicut Partitioning—0
Cut out the annotator, keep the cutout: better segmentation with weak supervision—0
Cutting-Splicing data augmentation: A novel technology for medical image segmentation—0
CVFC: Attention-Based Cross-View Feature Consistency for Weakly Supervised Semantic Segmentation of Pathology Images—0
D2-MLP: Dynamic Decomposed MLP Mixer for Medical Image Segmentation—0
D^2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video—0
DADU: Dual Attention-based Deep Supervised UNet for Automated Semantic Segmentation of Cardiac Images—0
Dam Burst: A region-merging-based image segmentation method—0
Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime—0
DaSeGAN: Domain Adaptation for Segmentation Tasks via Generative Adversarial Networks—0
Data Adaptive Few-shot Multi Label Segmentation with Foundation Model—0
Data Augmentation using Feature Generation for Volumetric Medical Images—0
Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical Image Segmentation—0
Data-Driven Deep Supervision for Medical Image Segmentation—0
Data-Driven Segmentation of Post-mortem Iris Images—0
Data-driven Verification of DNNs for Object Recognition—0
Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation—0
Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning—0
Data privacy protection in microscopic image analysis for material data mining—0
Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?—0
Data variation-aware medical image segmentation—0
Day-Night Adaptation: An Innovative Source-free Adaptation Framework for Medical Image Segmentation—0
DCELANM-Net:Medical Image Segmentation based on Dual Channel Efficient Layer Aggregation Network with Learner—0
DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation—0
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples—0
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images—0
Deep Active Contours Using Locally Controlled Distance Vector Flow—0
Deep-ASPECTS: A Segmentation-Assisted Model for Stroke Severity Measurement—0
Deep Attention Unet: A Network Model with Global Feature Perception Ability—0
Deep Bayesian U-Nets for Efficient, Robust and Reliable Post-Disaster Damage Localization—0
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All datasetsMSD (Mirror Segmentation Dataset)PMDMAS3KPascal Panoptic PartsRMASPASCAL VOCHuTu 80MARIDACOCO val2017ImageNetMSD HeartOxfordPets

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SAM2-UNetIoU0.92—Unverified
2HetNetIoU0.83—Unverified
3PMDIoU0.82—Unverified
4SANetIoU0.8—Unverified
5MirrorNetIoU0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1SAM2-UNetIoU0.73—Unverified
2HetNetIoU0.69—Unverified
3SANetIoU0.67—Unverified
4PMDIoU0.66—Unverified
5MirrorNetIoU0.59—Unverified
#ModelMetricClaimedVerifiedStatus
1SAM2-UNetmIoU0.8—Unverified
2MAS-SAMmIoU0.79—Unverified
3MASNetmIoU0.74—Unverified
4ZoomNetmIoU0.74—Unverified
#ModelMetricClaimedVerifiedStatus
1HIPIE (ViT-H)mIoUPartS63.8—Unverified
2PPSmIoUPartS58.6—Unverified
3HIPIE (ResNet-50)mIoUPartS57.2—Unverified
4JPPFmIoUPartS54.4—Unverified
#ModelMetricClaimedVerifiedStatus
1MAS-SAMmIoU0.74—Unverified
2SAM2-UNetmIoU0.74—Unverified
3MASNetmIoU0.73—Unverified
4ZoomNetmIoU0.73—Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4-CmIoU63.6—Unverified
2OneNete,4-SmAP0.552.75—Unverified
3OneNeted,4mIoU14.9—Unverified
#ModelMetricClaimedVerifiedStatus
1UNetRDice0.98—Unverified
2PALEDDice0.98—Unverified
#ModelMetricClaimedVerifiedStatus
1ResAttUNetIoU0.67—Unverified
2UNetIoU0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1SynCo (ResNet-50) 200epmask AP35.4—Unverified
#ModelMetricClaimedVerifiedStatus
1MobileOne-S0GFLOPs0.28—Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4mIoU6.6—Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4-CDice Score0.97—Unverified