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 1301–1350 of 5035 papers

TitleStatusHype
Color Image Segmentation using Adaptive Particle Swarm Optimization and Fuzzy C-means—0
A review of individual tree crown detection and delineation from optical remote sensing images—0
A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements—0
Color Image Segmentation Metrics—0
Color image segmentation based on a convex K-means approach—0
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation—0
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks—0
Collective Robustness Certificates—0
A Review of Artificial Intelligence Technologies for Early Prediction of Alzheimer's Disease—0
A General Framework for Complex Network-Based Image Segmentation—0
Distribution-Aware Replay for Continual MRI Segmentation—0
EmoCAM: Toward Understanding What Drives CNN-based Emotion Recognition—0
Collaborative Position Reasoning Network for Referring Image Segmentation—0
Collaborative Learning for Annotation-Efficient Volumetric MR Image Segmentation—0
A review: Deep learning for medical image segmentation using multi-modality fusion—0
Collaborative Boundary-aware Context Encoding Networks for Error Map Prediction—0
CoFiNet: Unveiling Camouflaged Objects with Multi-Scale Finesse—0
A Restricted-Domain Dual Formulation for Two-Phase Image Segmentation—0
3DRef: 3D Dataset and Benchmark for Reflection Detection in RGB and Lidar Data—0
CoCo DistillNet: a Cross-layer Correlation Distillation Network for Pathological Gastric Cancer Segmentation—0
A Comprehensive Survey of Transformers for Computer Vision—0
CNN-Transformer Rectified Collaborative Learning for Medical Image Segmentation—0
CNN in CT Image Segmentation: Beyound Loss Function for Expoliting Ground Truth Images—0
A Regularized Convolutional Neural Network for Semantic Image Segmentation—0
Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds—0
CNN-based Semantic Segmentation using Level Set Loss—0
A regularization-based approach for unsupervised image segmentation—0
A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trends—0
CNN-Based Deep Architecture for Reinforced Concrete Delamination Segmentation Through Thermography—0
CNN-aware Binary Map for General Semantic Segmentation—0
A fully automated framework for lung tumour detection, segmentation and analysis—0
EMDS-5: Environmental Microorganism Image Dataset Fifth Version for Multiple Image Analysis Tasks—0
Are foundation models efficient for medical image segmentation?—0
AFTer-UNet: Axial Fusion Transformer UNet for Medical Image Segmentation—0
EMDS-6: Environmental Microorganism Image Dataset Sixth Version for Image Denoising, Segmentation, Feature Extraction, Classification and Detection Methods Evaluation—0
Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging—0
CM-MaskSD: Cross-Modality Masked Self-Distillation for Referring Image Segmentation—0
Are conditional GANs explicitly conditional?—0
A Comprehensive Study on Medical Image Segmentation using Deep Neural Networks—0
C-MADA: Unsupervised Cross-Modality Adversarial Domain Adaptation framework for medical Image Segmentation—0
Clustering using Vector Membership: An Extension of the Fuzzy C-Means Algorithm—0
A Recent Survey of Vision Transformers for Medical Image Segmentation—0
3D Randomized Connection Network with Graph-based Label Inference—0
Clustering on the Edge: Learning Structure in Graphs—0
Clustering evolving data using kernel-based methods—0
A Random Point Initialization Approach to Image Segmentation with Variational Level-sets—0
A Formalization of Image Vectorization by Region Merging—0
ELEV-VISION-SAM: Integrated Vision Language and Foundation Model for Automated Estimation of Building Lowest Floor Elevation—0
Clustering Approach Towards Image Segmentation: An Analytical Study—0
A Radiomics-Incorporated Deep Ensemble Learning Model for Multi-Parametric MRI-based Glioma 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