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 33263350 of 5035 papers

TitleStatusHype
Semantic Segmentation With Multi Scale Spatial Attention For Self Driving Cars0
Semi-Automated Segmentation of Geoscientific Data Using Superpixels0
Semi-KAN: KAN Provides an Effective Representation for Semi-Supervised Learning in Medical Image Segmentation0
SEMI-PointRend: Improved Semiconductor Wafer Defect Classification and Segmentation as Rendering0
Semi-Siamese Network for Robust Change Detection Across Different Domains with Applications to 3D Printing0
Semi-Supervised and Self-Supervised Collaborative Learning for Prostate 3D MR Image Segmentation0
Semi-Supervised Domain Adaptation for Semantic Segmentation of Roads from Satellite Images0
Semi-Supervised Domain Adaptation via Adaptive and Progressive Feature Alignment0
Semi-supervised few-shot learning for medical image segmentation0
Semi-Supervised Image-to-Image Translation0
Semi-Supervised Learning for Eye Image Segmentation0
Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation0
Semi-Supervised Medical Image Segmentation via Learning Consistency under Transformations0
Semi-supervised Medical Image Segmentation through Dual-task Consistency0
Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer0
Semi-supervised Medical Image Segmentation via Geometry-aware Consistency Training0
Semi-Supervised Medical Image Segmentation with Co-Distribution Alignment0
Semi-Supervised Medical Image Segmentation via Knowledge Mining from Large Models0
Semi-Supervised Multi-Organ Segmentation through Quality Assurance Supervision0
Semi-Supervised Multi-Organ Segmentation via Deep Multi-Planar Co-Training0
Semi-supervised Node Splitting for Random Forest Construction0
Semi-Supervised Normalized Cuts for Image Segmentation0
Semi-supervised segmentation of land cover images using nonlinear canonical correlation analysis with multiple features and t-SNE0
Semi-Supervised Segmentation via Embedding Matching0
Semi-Supervised Semantic Segmentation Based on Pseudo-Labels: A Survey0
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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