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 1651–1700 of 5035 papers

TitleStatusHype
End-to-End Trainable Deep Active Contour Models for Automated Image Segmentation: Delineating Buildings in Aerial Imagery—0
Capsules for Biomedical Image Segmentation—0
Computer-Vision Benchmark Segment-Anything Model (SAM) in Medical Images: Accuracy in 12 Datasets—0
EAA-Net: Rethinking the Autoencoder Architecture with Intra-class Features for Medical Image Segmentation—0
Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance—0
Enhanced Uncertainty Estimation in Ultrasound Image Segmentation with MSU-Net—0
Cardiac MRI Image Segmentation for Left Ventricle and Right Ventricle using Deep Learning—0
A Novel Distance-Based Metric for Quality Assessment in Image Segmentation—0
Cardiac MR Image Segmentation Techniques: an overview—0
Enhancing DeepLabV3+ to Fuse Aerial and Satellite Images for Semantic Segmentation—0
Enhancing Foreground Boundaries for Medical Image Segmentation—0
CardiacNET: Segmentation of Left Atrium and Proximal Pulmonary Veins from MRI Using Multi-View CNN—0
Brain Tumor Detection Based on Bilateral Symmetry Information—0
Deep models for stroke segmentation: do complex architectures always perform better?—0
A Dual-fusion Semantic Segmentation Framework With GAN For SAR Images—0
BrainSegDMlF: A Dynamic Fusion-enhanced SAM for Brain Lesion Segmentation—0
Dynamic Multiscale Tree Learning Using Ensemble Strong Classifiers for Multi-label Segmentation of Medical Images with Lesions—0
Freeze the backbones: A Parameter-Efficient Contrastive Approach to Robust Medical Vision-Language Pre-training—0
Brain MRI Segmentation using Rule-Based Hybrid Approach—0
An Image Segmentation Model Based on a Variational Formulation—0
Car Segmentation and Pose Estimation using 3D Object Models—0
ACSeg: Adaptive Conceptualization for Unsupervised Semantic Segmentation—0
Enhancing Rock Image Segmentation in Digital Rock Physics: A Fusion of Generative AI and State-of-the-Art Neural Networks—0
Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentation—0
Dynamically evolving segment anything model with continuous learning for medical image segmentation—0
Enhancing Semantic Segmentation with Adaptive Focal Loss: A Novel Approach—0
Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization—0
DyCON: Dynamic Uncertainty-aware Consistency and Contrastive Learning for Semi-supervised Medical Image Segmentation—0
An image segmentation algorithm for measurement of flotation froth bubble size distributions—0
ADS_UNet: A Nested UNet for Histopathology Image Segmentation—0
BoxNet: Deep Learning Based Biomedical Image Segmentation Using Boxes Only Annotation—0
Ensembling Low Precision Models for Binary Biomedical Image Segmentation—0
Entropy Based Cartoon Texture Separation—0
Entropy-based Guidance of Deep Neural Networks for Accelerated Convergence and Improved Performance—0
Catalyzing Clinical Diagnostic Pipelines Through Volumetric Medical Image Segmentation Using Deep Neural Networks: Past, Present, & Future—0
Entropy Minimization for Convex Relaxation Approaches—0
Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures—0
EPL: Evidential Prototype Learning for Semi-supervised Medical Image Segmentation—0
FreeSeg-Diff: Training-Free Open-Vocabulary Segmentation with Diffusion Models—0
Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data—0
Error-tolerant Scribbles Based Interactive Image Segmentation—0
E-SAM: Training-Free Segment Every Entity Model—0
Box-Adapt: Domain-Adaptive Medical Image Segmentation using Bounding BoxSupervision—0
ESDMR-Net: A Lightweight Network With Expand-Squeeze and Dual Multiscale Residual Connections for Medical Image Segmentation—0
FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation—0
Freestyle Sketch-in-the-Loop Image Segmentation—0
FreqU-FNet: Frequency-Aware U-Net for Imbalanced Medical Image Segmentation—0
CausalCellSegmenter: Causal Inference inspired Diversified Aggregation Convolution for Pathology Image Segmentation—0
Fully Automated Organ Segmentation in Male Pelvic CT Images—0
Gated CRF Loss for Weakly Supervised Semantic 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