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Segmentation

Papers

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Showing 4501–4525 of 13072 papers

TitleStatusHype
Robust thalamic nuclei segmentation from T1-weighted MRICode1
CoMaL: Conditional Maximum Likelihood Approach to Self-supervised Domain Adaptation in Long-tail Semantic Segmentation—0
Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene UnderstandingCode2
MVP-SEG: Multi-View Prompt Learning for Open-Vocabulary Semantic Segmentation—0
Tailored Multi-Organ Segmentation with Model Adaptation and Ensemble—0
TUM-FAÇADE: Reviewing and enriching point cloud benchmarks for façade segmentationCode1
CROVIA: Seeing Drone Scenes from Car Perspective via Cross-View Adaptation—0
Segment Everything Everywhere All at OnceCode1
iResSENet: An Accurate Convolutional Neural Network for Retinal Blood Vessel SegmentationCode0
DeepSegmenter: Temporal Action Localization for Detecting Anomalies in Untrimmed Naturalistic Driving VideosCode0
Boosting Video Object Segmentation via Space-time Correspondence LearningCode1
DynaMITe: Dynamic Query Bootstrapping for Multi-object Interactive Segmentation Transformer—0
Deep learning based ECG segmentation for delineation of diverse arrhythmias—0
STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-trainingCode0
Leveraging triplet loss for unsupervised action segmentationCode1
[CLS] Token is All You Need for Zero-Shot Semantic Segmentation—0
Tracking by 3D Model Estimation of Unknown Objects in Videos—0
Improving Segmentation of Objects with Varying Sizes in Biomedical Images using Instance-wise and Center-of-Instance Segmentation Loss FunctionCode1
Neural Field Conditioning Strategies for 2D Semantic Segmentation—0
UniverSeg: Universal Medical Image SegmentationCode2
DUFormer: Solving Power Line Detection Task in Aerial Images using Semantic Segmentation—0
Few Shot Semantic Segmentation: a review of methodologies, benchmarks, and open challenges—0
Unifying and Personalizing Weakly-supervised Federated Medical Image Segmentation via Adaptive Representation and AggregationCode2
SAMM (Segment Any Medical Model): A 3D Slicer Integration to SAMCode2
Automated computed tomography and magnetic resonance imaging segmentation using deep learning: a beginner's guideCode1
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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