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 3051–3100 of 5035 papers

TitleStatusHype
R2U++: A Multiscale Recurrent Residual U-Net with Dense Skip Connections for Medical Image Segmentation—0
Radiological images and machine learning: trends, perspectives, and prospects—0
Radio U-Net: a convolutional neural network to detect diffuse radio sources in galaxy clusters and beyond—0
Radious: Unveiling the Enigma of Dental Radiology with BEIT Adaptor and Mask2Former in Semantic Segmentation—0
RadSAM: Segmenting 3D radiological images with a 2D promptable model—0
RAFT: Robust Augmentation of FeaTures for Image Segmentation—0
Railway LiDAR semantic segmentation based on intelligent semi-automated data annotation—0
RAIS: Robust and Accurate Interactive Segmentation via Continual Learning—0
Random-coupled Neural Network—0
Randomized Dimension Reduction with Statistical Guarantees—0
Random Style Transfer based Domain Generalization Networks Integrating Shape and Spatial Information—0
Rapid model transfer for medical image segmentation via iterative human-in-the-loop update: from labelled public to unlabelled clinical datasets for multi-organ segmentation in CT—0
FlexiFly: Interfacing the Physical World with Foundation Models Empowered by Reconfigurable Drone Systems—0
RaSP: Relation-aware Semantic Prior for Weakly Supervised Incremental Segmentation—0
Rate-My-LoRA: Efficient and Adaptive Federated Model Tuning for Cardiac MRI Segmentation—0
Real2Code: Reconstruct Articulated Objects via Code Generation—0
Realistic Data Enrichment for Robust Image Segmentation in Histopathology—0
Real-Time and Robust Method for Hand Gesture Recognition System Based on Cross-Correlation Coefficient—0
Real-Time High-Performance Semantic Image Segmentation of Urban Street Scenes—0
Real-Time Human Motion Capture with Multiple Depth Cameras—0
Real-Time Multi-Modal Semantic Fusion on Unmanned Aerial Vehicles—0
Real-Time Multi-Modal Semantic Fusion on Unmanned Aerial Vehicles with Label Propagation for Cross-Domain Adaptation—0
Real-time Prediction of Segmentation Quality—0
Real-time Seafloor Segmentation and Mapping—0
Real-time Semantic Image Segmentation via Spatial Sparsity—0
Real-Time Semantic Segmentation: A Brief Survey & Comparative Study in Remote Sensing—0
Recent Advances of Generic Object Detection with Deep Learning: A Review—0
Recent progress in semantic image segmentation—0
ReCoRe: Regularized Contrastive Representation Learning of World Model—0
Recurrent Fully Convolutional Networks for Video Segmentation—0
Recurrent Segmentation for Variable Computational Budgets—0
Recyclable Waste Identification Using CNN Image Recognition and Gaussian Clustering—0
RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement—0
Redesigning Out-of-Distribution Detection on 3D Medical Images—0
Reducing Domain Gap in Frequency and Spatial domain for Cross-modality Domain Adaptation on Medical Image Segmentation—0
Referring Image Segmentation by Generative Adversarial Learning—0
Referring Remote Sensing Image Segmentation via Bidirectional Alignment Guided Joint Prediction—0
Refer to Anything with Vision-Language Prompts—0
Reflection methods for user-friendly submodular optimization—0
RefSAM3D: Adapting SAM with Cross-modal Reference for 3D Medical Image Segmentation—0
Regional Active Contours based on Variational level sets and Machine Learning for Image Segmentation—0
Regional Interactive Image Segmentation Networks—0
Region-based Segmentation and Object Detection—0
Region Growing with Convolutional Neural Networks for Biomedical Image Segmentation—0
Region-Guided Attack on the Segment Anything Model (SAM)—0
Regression of Instance Boundary by Aggregated CNN and GCN—0
Regular Partitions and Their Use in Structural Pattern Recognition—0
Reinforcement Learning for Ultrasound Image Analysis A Comprehensive Review of Advances and Applications—0
Re-initialization-free Level Set Method via Molecular Beam Epitaxy Equation Regularization for Image Segmentation—0
Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization—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