SOTAVerified

Segmentation

Papers

Showing 15261550 of 13072 papers

TitleStatusHype
Applications of Deep Learning in Fundus Images: A ReviewCode1
Geometrically-driven Aggregation for Zero-shot 3D Point Cloud UnderstandingCode1
AutoFocusFormer: Image Segmentation off the GridCode1
GeoSegNet: Point Cloud Semantic Segmentation via Geometric Encoder-Decoder ModelingCode1
AutoGPart: Intermediate Supervision Search for Generalizable 3D Part SegmentationCode1
GFF: Gated Fully Fusion for Semantic SegmentationCode1
GFNet: Geometric Flow Network for 3D Point Cloud Semantic SegmentationCode1
Advancing UWF-SLO Vessel Segmentation with Source-Free Active Domain Adaptation and a Novel Multi-Center DatasetCode1
Glass Segmentation with RGB-Thermal Image PairsCode1
Cross-View Image Synthesis using Conditional GANsCode1
Cross-view Transformers for real-time Map-view Semantic SegmentationCode1
AISFormer: Amodal Instance Segmentation with TransformerCode1
Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic SegmentationCode1
GNeSF: Generalizable Neural Semantic FieldsCode1
Cross-Modal Progressive Comprehension for Referring SegmentationCode1
GPU-Net: Lightweight U-Net with more diverse featuresCode1
Automated Chest CT Image Segmentation of COVID-19 Lung Infection based on 3D U-NetCode1
Automated computed tomography and magnetic resonance imaging segmentation using deep learning: a beginner's guideCode1
Cross-Modality Multi-Atlas Segmentation via Deep Registration and Label FusionCode1
Gradient-Weighted Feature Back-Projection: A Fast Alternative to Feature Distillation in 3D Gaussian SplattingCode1
GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video SegmentationCode1
Cross Prompting Consistency with Segment Anything Model for Semi-supervised Medical Image SegmentationCode1
Cross-Modal Conditioned Reconstruction for Language-guided Medical Image SegmentationCode1
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea SegmentationCode1
Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial LearningCode1
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Benchmark Results

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