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 4501–4550 of 5035 papers

TitleStatusHype
A semi-supervised fuzzy GrowCut algorithm to segment and classify regions of interest of mammographic images—0
Splenomegaly Segmentation using Global Convolutional Kernels and Conditional Generative Adversarial NetworksCode0
Mix-and-Match Tuning for Self-Supervised Semantic Segmentation—0
A 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation—0
Real-time Semantic Image Segmentation via Spatial Sparsity—0
Automatic Spine Segmentation using Convolutional Neural Network via Redundant Generation of Class Labels for 3D Spine Modeling—0
Multi-stream 3D FCN with Multi-scale Deep Supervision for Multi-modality Isointense Infant Brain MR Image Segmentation—0
Recurrent Segmentation for Variable Computational Budgets—0
Automatic Color Image Segmentation Using a Square Elemental Region-Based Seeded Region Growing and Merging Method—0
Efficient and Invariant Convolutional Neural Networks for Dense Prediction—0
Cost-Effective Active Learning for Melanoma SegmentationCode0
W-Net: A Deep Model for Fully Unsupervised Image SegmentationCode1
Robust Seed Mask Generation for Interactive Image Segmentation—0
DLTK: State of the Art Reference Implementations for Deep Learning on Medical ImagesCode0
Fast Recurrent Fully Convolutional Networks for Direct Perception in Autonomous Driving—0
Language-Based Image Editing with Recurrent Attentive ModelsCode0
Conditional Random Field and Deep Feature Learning for Hyperspectral Image Segmentation—0
3D Randomized Connection Network with Graph-based Label Inference—0
Curve-Structure Segmentation from Depth Maps: A CNN-based Approach and Its Application to Exploring Cultural Heritage Objects—0
Region growing using superpixels with learned shape prior.Code0
Supervised and unsupervised segmentation using superpixels, model estimation, and Graph Cut.Code0
Image Segmentation of Multi-Shaped Overlapping Objects—0
Ω-Net (Omega-Net): Fully Automatic, Multi-View Cardiac MR Detection, Orientation, and Segmentation with Deep Neural Networks—0
Segmentation-by-Detection: A Cascade Network for Volumetric Medical Image Segmentation—0
Medical Image Segmentation Based on Multi-Modal Convolutional Neural Network: Study on Image Fusion Schemes—0
A Connection between Feed-Forward Neural Networks and Probabilistic Graphical Models—0
SEGMENT3D: A Web-based Application for Collaborative Segmentation of 3D images used in the Shoot Apical Meristem—0
Improved Workflow for Unsupervised Multiphase Image Segmentation—0
Image Segmentation and Classification for Sickle Cell Disease using Deformable U-Net—0
Historical Document Image Segmentation with LDA-Initialized Deep Neural NetworksCode0
Function Norms and Regularization in Deep Networks—0
VisDA: The Visual Domain Adaptation ChallengeCode1
A Finite Element Computational Framework for Active Contours on Graphs—0
Interactive Medical Image Segmentation using Deep Learning with Image-specific Fine-tuning—0
Texture Fuzzy Segmentation using Skew Divergence Adaptive Affinity Functions—0
FPGA based Parallelized Architecture of Efficient Graph based Image Segmentation Algorithm—0
Learning Affinity via Spatial Propagation Network—0
Learning Affinity via Spatial Propagation Networks—0
Regional Interactive Image Segmentation Networks—0
Deep Dual Learning for Semantic Image Segmentation—0
The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes—0
Fast Barcode Retrieval for Consensus Contouring—0
Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks—0
Possibilistic Fuzzy Local Information C-Means for Sonar Image Segmentation—0
Neural Multi-Atlas Label Fusion: Application to Cardiac MR Images—0
Neural networks for topology optimizationCode0
Learning to Label Affordances from Simulated and Real Data—0
H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT VolumesCode0
A First Derivative Potts Model for Segmentation and Denoising Using ILP—0
SegFlow: Joint Learning for Video Object Segmentation and Optical FlowCode0
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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