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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3676–3700 of 5035 papers

TitleStatusHype
D^2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video—0
DADU: Dual Attention-based Deep Supervised UNet for Automated Semantic Segmentation of Cardiac Images—0
Dam Burst: A region-merging-based image segmentation method—0
Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime—0
DaSeGAN: Domain Adaptation for Segmentation Tasks via Generative Adversarial Networks—0
Data Adaptive Few-shot Multi Label Segmentation with Foundation Model—0
Data Augmentation using Feature Generation for Volumetric Medical Images—0
Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical Image Segmentation—0
Data-Driven Deep Supervision for Medical Image Segmentation—0
Data-Driven Segmentation of Post-mortem Iris Images—0
Data-driven Verification of DNNs for Object Recognition—0
Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation—0
Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning—0
Data privacy protection in microscopic image analysis for material data mining—0
Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?—0
Data variation-aware medical image segmentation—0
Day-Night Adaptation: An Innovative Source-free Adaptation Framework for Medical Image Segmentation—0
DCELANM-Net:Medical Image Segmentation based on Dual Channel Efficient Layer Aggregation Network with Learner—0
DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation—0
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples—0
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images—0
Deep Active Contours Using Locally Controlled Distance Vector Flow—0
Deep-ASPECTS: A Segmentation-Assisted Model for Stroke Severity Measurement—0
Deep Attention Unet: A Network Model with Global Feature Perception Ability—0
Deep Bayesian U-Nets for Efficient, Robust and Reliable Post-Disaster Damage Localization—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