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

Showing 576600 of 5035 papers

TitleStatusHype
Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking SystemsCode1
Deep Instruction Tuning for Segment Anything ModelCode1
Automated computed tomography and magnetic resonance imaging segmentation using deep learning: a beginner's guideCode1
Automated Segmentation of Optical Coherence Tomography Angiography Images: Benchmark Data and Clinically Relevant MetricsCode1
Deep clustering: Discriminative embeddings for segmentation and separationCode1
DeepCut: Unsupervised Segmentation using Graph Neural Networks ClusteringCode1
DenoiseRep: Denoising Model for Representation LearningCode1
Amodal Ground Truth and Completion in the WildCode1
Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image SegmentationCode1
Decomposing 3D Scenes into Objects via Unsupervised Volume SegmentationCode1
AutoFocusFormer: Image Segmentation off the GridCode1
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image SegmentationCode1
DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images SegmentationCode1
Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and GrounderCode1
DatasetGAN: Efficient Labeled Data Factory with Minimal Human EffortCode1
Adapting Segment Anything Model (SAM) through Prompt-based Learning for Enhanced Protein Identification in Cryo-EM MicrographsCode1
Automated Chest CT Image Segmentation of COVID-19 Lung Infection based on 3D U-NetCode1
DA-TransUNet: Integrating Spatial and Channel Dual Attention with Transformer U-Net for Medical Image SegmentationCode1
Deep ContourFlow: Advancing Active Contours with Deep LearningCode1
Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentationCode1
Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentationCode1
AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image SegmentationCode1
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFsCode1
Deep Multi-Threshold Spiking-UNet for Image ProcessingCode1
Auto-Compressing Subset Pruning for Semantic Image SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SAM2-UNetIoU0.92Unverified
2HetNetIoU0.83Unverified
3PMDIoU0.82Unverified
4SANetIoU0.8Unverified
5MirrorNetIoU0.79Unverified
#ModelMetricClaimedVerifiedStatus
1SAM2-UNetIoU0.73Unverified
2HetNetIoU0.69Unverified
3SANetIoU0.67Unverified
4PMDIoU0.66Unverified
5MirrorNetIoU0.59Unverified
#ModelMetricClaimedVerifiedStatus
1SAM2-UNetmIoU0.8Unverified
2MAS-SAMmIoU0.79Unverified
3MASNetmIoU0.74Unverified
4ZoomNetmIoU0.74Unverified
#ModelMetricClaimedVerifiedStatus
1HIPIE (ViT-H)mIoUPartS63.8Unverified
2PPSmIoUPartS58.6Unverified
3HIPIE (ResNet-50)mIoUPartS57.2Unverified
4JPPFmIoUPartS54.4Unverified
#ModelMetricClaimedVerifiedStatus
1MAS-SAMmIoU0.74Unverified
2SAM2-UNetmIoU0.74Unverified
3MASNetmIoU0.73Unverified
4ZoomNetmIoU0.73Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4-CmIoU63.6Unverified
2OneNete,4-SmAP0.552.75Unverified
3OneNeted,4mIoU14.9Unverified
#ModelMetricClaimedVerifiedStatus
1UNetRDice0.98Unverified
2PALEDDice0.98Unverified
#ModelMetricClaimedVerifiedStatus
1ResAttUNetIoU0.67Unverified
2UNetIoU0.57Unverified
#ModelMetricClaimedVerifiedStatus
1SynCo (ResNet-50) 200epmask AP35.4Unverified
#ModelMetricClaimedVerifiedStatus
1MobileOne-S0GFLOPs0.28Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4mIoU6.6Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4-CDice Score0.97Unverified