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 2551–2600 of 5035 papers

TitleStatusHype
Style Augmentation improves Medical Image Segmentation—0
Style Curriculum Learning for Robust Medical Image Segmentation—0
Style-invariant Cardiac Image Segmentation with Test-time Augmentation—0
Data augmentation in microscopic images for material data mining—0
Subspace Learning in The Presence of Sparse Structured Outliers and Noise—0
Supervision by Denoising for Medical Image Segmentation—0
Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation—0
Suggestive Annotation of Brain MR Images with Gradient-guided Sampling—0
Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling—0
SuperCL: Superpixel Guided Contrastive Learning for Medical Image Segmentation Pre-training—0
Superdifferential Cuts for Binary Energies—0
SuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches—0
Superpixel-Guided Label Softening for Medical Image Segmentation—0
Superpixel Pre-Segmentation of HER2 Slides for Efficient Annotation—0
Superpixel Segmentation Using Linear Spectral Clustering—0
Super Resolution Convolutional Neural Network Models for Enhancing Resolution of Rock Micro-CT Images—0
Supervised Image Segmentation for High Dynamic Range Imaging—0
Support-Query Prototype Fusion Network for Few-shot Medical Image Segmentation—0
Support vector machine classification of dimensionally reduced structural MRI images for dementia—0
Support Vector Machine Guided Reproducing Kernel Particle Method for Image-Based Modeling of Microstructures—0
Surf-CDM: Score-Based Surface Cold-Diffusion Model For Medical Image Segmentation—0
Survey on Semantic Stereo Matching / Semantic Depth Estimation—0
SUSAN: Segment Unannotated image Structure using Adversarial Network—0
SwinCross: Cross-modal Swin Transformer for Head-and-Neck Tumor Segmentation in PET/CT Images—0
Swin Deformable Attention Hybrid U-Net for Medical Image Segmentation—0
Swin UNETR segmentation with automated geometry filtering for biomechanical modeling of knee joint cartilage—0
SwipeCut: Interactive Segmentation with Diversified Seed Proposals—0
Switched auxiliary loss for robust training of transformer models for histopathological image segmentation—0
SX-Stitch: An Efficient VMS-UNet Based Framework for Intraoperative Scoliosis X-Ray Image Stitching—0
SydneyScapes: Image Segmentation for Australian Environments—0
Symmetry-invariant optimization in deep networks—0
Synchronizing Vision and Language: Bidirectional Token-Masking AutoEncoder for Referring Image Segmentation—0
Synchronous Image-Label Diffusion Probability Model with Application to Stroke Lesion Segmentation on Non-contrast CT—0
Synergy-Guided Regional Supervision of Pseudo Labels for Semi-Supervised Medical Image Segmentation—0
SynergyNet: Bridging the Gap between Discrete and Continuous Representations for Precise Medical Image Segmentation—0
SynNet: Structure-Preserving Fully Convolutional Networks for Medical Image Synthesis—0
Generative Synthetic Augmentation using Label-to-Image Translation for Nuclei Image Segmentation—0
Synthetic data enables faster annotation and robust segmentation for multi-object grasping in clutter—0
Synthetic Data for Semantic Image Segmentation of Imagery of Unmanned Spacecraft—0
Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation—0
Synthetic-to-real Composite Semantic Segmentation in Additive Manufacturing—0
SynthFM: Training Modality-agnostic Foundation Models for Medical Image Segmentation without Real Medical Data—0
Systematic Clinical Evaluation of A Deep Learning Method for Medical Image Segmentation: Radiosurgery Application—0
Systematic review of image segmentation using complex networks—0
TAGS: 3D Tumor-Adaptive Guidance for SAM—0
Taming Mambas for Voxel Level 3D Medical Image Segmentation—0
Tangles and Hierarchical Clustering—0
Task-Aware Low-Rank Adaptation of Segment Anything Model—0
Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation—0
Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation—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