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 3001–3050 of 5035 papers

TitleStatusHype
Progressively Diffused Networks for Semantic Image Segmentation—0
Progressive Mirror Detection—0
Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT—0
ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation—0
ProMamba: Prompt-Mamba for polyp segmentation—0
Promoting Segment Anything Model towards Highly Accurate Dichotomous Image Segmentation—0
Prompt2SegCXR:Prompt to Segment All Organs and Diseases in Chest X-rays—0
Prompt-Based Segmentation at Multiple Resolutions and Lighting Conditions using Segment Anything Model 2—0
Prompt-Based Tuning of Transformer Models for Multi-Center Medical Image Segmentation of Head and Neck Cancer—0
Prompt-Driven Referring Image Segmentation with Instance Contrasting—0
Prompt Engineering in Segment Anything Model: Methodologies, Applications, and Emerging Challenges—0
Prompt-Guided Dual-Path UNet with Mamba for Medical Image Segmentation—0
Propagating Semantic Labels in Video Data—0
PAM: A Propagation-Based Model for Segmenting Any 3D Objects across Multi-Modal Medical Images—0
ProSAM: Enhancing the Robustness of SAM-based Visual Reference Segmentation with Probabilistic Prompts—0
Prostate Segmentation using 2D Bridged U-net—0
Prototype-Based Approach for One-Shot Segmentation of Brain Tumors using Few-Shot Learning—0
Prototype-Based Image Prompting for Weakly Supervised Histopathological Image Segmentation—0
Prototype Correlation Matching and Class-Relation Reasoning for Few-Shot Medical Image Segmentation—0
PrPSeg: Universal Proposition Learning for Panoramic Renal Pathology Segmentation—0
PRS-Med: Position Reasoning Segmentation with Vision-Language Model in Medical Imaging—0
Pruning random resistive memory for optimizing analogue AI—0
Pseudo-Boolean Polynomials Approach To Edge Detection And Image Segmentation—0
PseudoClick: Interactive Image Segmentation with Click Imitation—0
PSO-UNet: Particle Swarm-Optimized U-Net Framework for Precise Multimodal Brain Tumor Segmentation—0
PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation—0
Pubic Symphysis-Fetal Head Segmentation Network Using BiFormer Attention Mechanism and Multipath Dilated Convolution—0
Push the Boundary of SAM: A Pseudo-label Correction Framework for Medical Segmentation—0
Pylon Model for Semantic Segmentation—0
Pyramid Architecture for Multi-Scale Processing in Point Cloud Segmentation—0
Pyramid Graph Networks With Connection Attentions for Region-Based One-Shot Semantic Segmentation—0
Pyramid Medical Transformer for Medical Image Segmentation—0
Q2A: Querying Implicit Fully Continuous Feature Pyramid to Align Features for Medical Image Segmentation—0
QIS : Interactive Segmentation via Quasi-Conformal Mappings—0
Q-learning optimization in a multi-agents system for image segmentation—0
Q-Segment: Segmenting Images In-Sensor for Vessel-Based Medical Diagnosis—0
Quality-Adaptive Split-Federated Learning for Segmenting Medical Images with Inaccurate Annotations—0
Quality-aware semi-supervised learning for CMR segmentation—0
Automatic quality control framework for more reliable integration of machine learning-based image segmentation into medical workflows—0
Quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation—0
Quantization of Deep Neural Networks for Accurate Edge Computing—0
Quantization of Fully Convolutional Networks for Accurate Biomedical Image Segmentation—0
Quantized Feature Distillation for Network Quantization—0
Quantum Edge Detection for Image Segmentation in Optical Environments—0
Quantum-enhanced unsupervised image segmentation for medical images analysis—0
Quantum Image Segmentation Based on Grayscale Morphology—0
QuantU-Net: Efficient Wearable Medical Imaging Using Bitwidth as a Trainable Parameter—0
QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge—0
QuFeX: Quantum feature extraction module for hybrid quantum-classical deep neural networks—0
R2U3D: Recurrent Residual 3D U-Net for Lung 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