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 38513875 of 5035 papers

TitleStatusHype
Microvasculature Segmentation in Human BioMolecular Atlas Program (HuBMAP)0
MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation0
Mind The Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation0
Minimizing Energy Costs in Deep Learning Model Training: The Gaussian Sampling Approach0
Minimum Class Confusion based Transfer for Land Cover Segmentation in Rural and Urban Regions0
MIRAM: Masked Image Reconstruction Across Multiple Scales for Breast Lesion Risk Prediction0
MiSuRe is all you need to explain your image segmentation0
Mitigating False Predictions In Unreasonable Body Regions0
Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals0
Mix-and-Match Tuning for Self-Supervised Semantic Segmentation0
MixCL: Pixel label matters to contrastive learning0
Mixed-Block Neural Architecture Search for Medical Image Segmentation0
Mixed Prototype Consistency Learning for Semi-supervised Medical Image Segmentation0
Mixed-Query Transformer: A Unified Image Segmentation Architecture0
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications to Parallel Machine Learning and Multi-Label Image Segmentation0
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications0
Mixed-Supervised Dual-Network for Medical Image Segmentation0
Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference0
Mixing Data Augmentation with Preserving Foreground Regions in Medical Image Segmentation0
MixModule: Mixed CNN Kernel Module for Medical Image Segmentation0
Mixture Modeling of Global Shape Priors and Autoencoding Local Intensity Priors for Left Atrium Segmentation0
Mixture-of-Shape-Experts (MoSE): End-to-End Shape Dictionary Framework to Prompt SAM for Generalizable Medical Segmentation0
Mixtures of Neural Cellular Automata: A Stochastic Framework for Growth Modelling and Self-Organization0
Mixup-Privacy: A simple yet effective approach for privacy-preserving segmentation0
MKIS-Net: A Light-Weight Multi-Kernel Network for Medical Image Segmentation0
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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