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 4326–4350 of 5035 papers

TitleStatusHype
Image Segmentation Based on Watershed and Edge Detection Techniques—0
Image Segmentation-based Unsupervised Multiple Objects Discovery—0
Image Segmentation by Cascaded Region Agglomeration—0
Image segmentation by optimal and hierarchical piecewise constant approximations—0
Image Segmentation by Size-Dependent Single Linkage Clustering of a Watershed Basin Graph—0
Image Segmentation by Uniform Color Clustering Approach and Benchmark Results—0
Image Segmentation for Fruit Detection and Yield Estimation in Apple Orchards—0
Image Segmentation For Improved Lossless Screen Content Compression—0
Image Segmentation for Radar Signal Deinterleaving Using Deep Learning—0
Image Segmentation from Shadow-Hints using Minimum Spanning Trees—0
Image Segmentation in Liquid Argon Time Projection Chamber Detector—0
Image Segmentation in Twenty Questions—0
Image Segmentation Methods for Non-destructive testing Applications—0
Image segmentation of cross-country scenes captured in IR spectrum—0
Image segmentation of liver stage malaria infection with spatial uncertainty sampling—0
Image Segmentation of Multi-Shaped Overlapping Objects—0
Image segmentation of treated and untreated tumor spheroids by Fully Convolutional Networks—0
Image Segmentation of Zona-Ablated Human Blastocysts—0
Image Segmentation to Distinguish Between Overlapping Human Chromosomes—0
Image Segmentation to Identify Safe Landing Zones for Unmanned Aerial Vehicles—0
Image Segmentation Using Frequency Locking of Coupled Oscillators—0
Image Segmentation Using Hybrid Representations—0
Image Segmentation using Multi-Threshold technique by Histogram Sampling—0
Image Segmentation Using Overlapping Group Sparsity—0
Image Segmentation Using Subspace Representation and Sparse Decomposition—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