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Segmentation

Papers

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Showing 2526–2550 of 13072 papers

TitleStatusHype
An Active Contour Model Driven By the Hybrid Signed Pressure Function—0
Learn and Search: An Elegant Technique for Object Lookup using Contrastive Learning—0
Dynamic U-Net: Adaptively Calibrate Features for Abdominal Multi-organ SegmentationCode0
BraSyn 2023 challenge: Missing MRI synthesis and the effect of different learning objectives—0
Beyond Pixels: Enhancing LIME with Hierarchical Features and Segmentation Foundation ModelsCode1
Simulation-Based Segmentation of Blood Vessels in Cerebral 3D OCTA Images—0
A cascaded deep network for automated tumor detection and segmentation in clinical PET imaging of diffuse large B-cell lymphoma—0
Shortcut Learning in Medical Image SegmentationCode0
Toward Robust Canine Cardiac Diagnosis: Deep Prototype Alignment Network-Based Few-Shot Segmentation in Veterinary Medicine—0
Average Calibration Error: A Differentiable Loss for Improved Reliability in Image SegmentationCode0
Skeleton Supervised Airway Segmentation—0
Refining Segmentation On-the-Fly: An Interactive Framework for Point Cloud Semantic Segmentation—0
3DRef: 3D Dataset and Benchmark for Reflection Detection in RGB and Lidar Data—0
A Segmentation Foundation Model for Diverse-type Tumors—0
Query-guided Prototype Evolution Network for Few-Shot Segmentation—0
Style Blind Domain Generalized Semantic Segmentation via Covariance Alignment and Semantic Consistence Contrastive LearningCode1
ClickVOS: Click Video Object SegmentationCode0
Mask-Enhanced Segment Anything Model for Tumor Lesion Semantic SegmentationCode1
FedFMS: Exploring Federated Foundation Models for Medical Image SegmentationCode2
Attention-guided Feature Distillation for Semantic Segmentation—0
LVIC: Multi-modality segmentation by Lifting Visual Info as Cue—0
From Registration Uncertainty to Segmentation Uncertainty—0
Out of the Room: Generalizing Event-Based Dynamic Motion Segmentation for Complex Scenes—0
Multi-Grained Cross-modal Alignment for Learning Open-vocabulary Semantic Segmentation from Text Supervision—0
Self and Mixed Supervision to Improve Training Labels for Multi-Class Medical Image Segmentation—0
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All datasetsSA-1B.MFSDMMFloodSimGas

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1unSAM+ (Semi-supervised)Average Precision42.8—Unverified
2SAMAverage Precision38.9—Unverified
#ModelMetricClaimedVerifiedStatus
1HNN10%20—Unverified
#ModelMetricClaimedVerifiedStatus
1ABANetF1 Score96.82—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50 + DeepLabV3+F1 score0.77—Unverified
#ModelMetricClaimedVerifiedStatus
1LangGasIoU0.69—Unverified