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 3801–3850 of 5035 papers

TitleStatusHype
Diagnostics in Semantic Segmentation—0
Diagonal Hierarchical Consistency Learning for Semi-supervised Medical Image Segmentation—0
DIAMANT: Dual Image-Attention Map Encoders For Medical Image Segmentation—0
Diff-CL: A Novel Cross Pseudo-Supervision Method for Semi-supervised Medical Image Segmentation—0
Differentiable Programming for Piecewise Polynomial Functions—0
Differentiable Projection for Constrained Deep Learning—0
Differentiable Rendering: A Survey—0
Differentiable Spline Approximations—0
Differential Privacy for Adaptive Weight Aggregation in Federated Tumor Segmentation—0
DiffPose: SpatioTemporal Diffusion Model for Video-Based Human Pose Estimation—0
DiffSeg: A Segmentation Model for Skin Lesions Based on Diffusion Difference—0
Diffuse-UDA: Addressing Unsupervised Domain Adaptation in Medical Image Segmentation with Appearance and Structure Aligned Diffusion Models—0
Diffusion based Zero-shot Medical Image-to-Image Translation for Cross Modality Segmentation—0
DIGEST: Deeply supervIsed knowledGE tranSfer neTwork learning for brain tumor segmentation with incomplete multi-modal MRI scans—0
Digitization of Raster Logs: A Deep Learning Approach—0
Dilated Balanced Cross Entropy Loss for Medical Image Segmentation—0
Dilated Convolutions in Neural Networks for Left Atrial Segmentation in 3D Gadolinium Enhanced-MRI—0
DiM: f-Divergence Minimization Guided Sharpness-Aware Optimization for Semi-supervised Medical Image Segmentation—0
Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation—0
Atomic number estimation of dual energy cargo radiographs using a semiempirical transparency model—0
Direct Estimation of Appearance Models for Segmentation—0
Direct White Matter Bundle Segmentation using Stacked U-Nets—0
Disaggregation of SMAP L3 Brightness Temperatures to 9km using Kernel Machines—0
Discover the Mysteries of the Maya: Selected Contributions from the Machine Learning Challenge & The Discovery Challenge Workshop at ECML PKDD 2021—0
Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs—0
Discrete-Continuous Gradient Orientation Estimation for Faster Image Segmentation—0
Discrete Signal Processing with Set Functions—0
Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes—0
Discriminatively Trained Sparse Code Gradients for Contour Detection—0
Discriminative Multi-Modal Feature Fusion for RGBD Indoor Scene Recognition—0
Discriminative Re-ranking of Diverse Segmentations—0
Disjunctive Normal Level Set: An Efficient Parametric Implicit Method—0
Disparity Image Segmentation For ADAS—0
Distilling effective supervision for robust medical image segmentation with noisy labels—0
Distributed Contrastive Learning for Medical Image Segmentation—0
Distributed Submodular Minimization via Block-Wise Updates and Communications—0
Distributed U-net model and Image Segmentation for Lung Cancer Detection—0
Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation—0
Distribution-aware Margin Calibration for Medical Image Segmentation—0
Diversity in Machine Learning—0
Diversity-Promoting Ensemble for Medical Image Segmentation—0
FocusNet++: Attentive Aggregated Transformations for Efficient and Accurate Medical Image Segmentation—0
D-LEMA: Deep Learning Ensembles from Multiple Annotations -- Application to Skin Lesion Segmentation—0
DmADs-Net: Dense multiscale attention and depth-supervised network for medical image segmentation—0
DMC-Net: Lightweight Dynamic Multi-Scale and Multi-Resolution Convolution Network for Pancreas Segmentation in CT Images—0
DMCNN: A Deep Multiscale Convolutional Neural Network Model for Medical Image Segmentation—0
DocBed: A Multi-Stage OCR Solution for Documents with Complex Layouts—0
DocSAM: Unified Document Image Segmentation via Query Decomposition and Heterogeneous Mixed Learning—0
Do Deep Neural Networks for Segmentation Understand Insideness?—0
Does Non-COVID19 Lung Lesion Help? Investigating Transferability in COVID-19 CT 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