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

Showing 35763600 of 5035 papers

TitleStatusHype
Computer Stereo Vision for Autonomous Driving0
Computing the Spatial Probability of Inclusion inside Partial Contours for Computer Vision Applications0
Concealed Object Segmentation with Hierarchical Coherence Modeling0
Concept Mask: Large-Scale Segmentation from Semantic Concepts0
CondenseUNet: A Memory-Efficient Condensely-Connected Architecture for Bi-ventricular Blood Pool and Myocardium Segmentation0
Conditional Conformal Risk Adaptation0
Conditional Random Field and Deep Feature Learning for Hyperspectral Image Segmentation0
Conditional Segmentation in Lieu of Image Registration0
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation0
Confidence Intervals for Performance Estimates in Brain MRI Segmentation0
Conformal confidence sets for biomedical image segmentation0
Conformal Lyapunov Optimization: Optimal Resource Allocation under Deterministic Reliability Constraints0
ConFUDA: Contrastive Fewshot Unsupervised Domain Adaptation for Medical Image Segmentation0
ConnectedUNets++: Mass Segmentation from Whole Mammographic Images0
Connections between Operator-splitting Methods and Deep Neural Networks with Applications in Image Segmentation0
Connectivity-Driven Parcellation Methods for the Human Cerebral Cortex0
Consensus Based Medical Image Segmentation Using Semi-Supervised Learning And Graph Cuts0
CONSIGN: Conformal Segmentation Informed by Spatial Groupings via Decomposition0
Constrained Deep Weak Supervision for Histopathology Image Segmentation0
Constrained Dominant sets and Its applications in computer vision0
Constrained Multiview Representation for Self-supervised Contrastive Learning0
Constraints as Features0
Context Driven Label Fusion for segmentation of Subcutaneous and Visceral Fat in CT Volumes0
ContextLoss: Context Information for Topology-Preserving Segmentation0
Contextual Hourglass Networks for Segmentation and Density Estimation0
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Benchmark Results

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