SOTAVerified

Segmentation

Papers

Showing 801825 of 13072 papers

TitleStatusHype
Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene UnderstandingCode1
A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and ProtocolsCode1
CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image SegmentationCode1
Cutting-edge 3D Medical Image Segmentation Methods in 2020: Are Happy Families All Alike?Code1
CV 3315 Is All You Need : Semantic Segmentation CompetitionCode1
Stitching, Fine-tuning, Re-training: A SAM-enabled Framework for Semi-supervised 3D Medical Image SegmentationCode1
A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial ImagesCode1
AlignSAM: Aligning Segment Anything Model to Open Context via Reinforcement LearningCode1
AlignSeg: Feature-Aligned Segmentation NetworksCode1
Cyclic Learning: Bridging Image-level Labels and Nuclei Instance SegmentationCode1
A Likelihood Ratio-Based Approach to Segmenting Unknown ObjectsCode1
D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention MechanismCode1
D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in VideosCode1
DAAIN: Detection of Anomalous and Adversarial Input using Normalizing FlowsCode1
Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional NetworksCode1
Alleviating Over-segmentation Errors by Detecting Action BoundariesCode1
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and CountingCode1
Comprehensive Comparison of Deep Learning Models for Lung and COVID-19 Lesion Segmentation in CT scansCode1
UVO Challenge on Video-based Open-World Segmentation 2021: 1st Place SolutionCode1
All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D SegmentationCode1
All you need are a few pixels: semantic segmentation with PixelPickCode1
DA Wand: Distortion-Aware Selection using Neural Mesh ParameterizationCode1
Anatomical and Diagnostic Bayesian Segmentation in Prostate MRI -Should Different Clinical Objectives Mandate Different Loss Functions?Code1
DC-Seg: Disentangled Contrastive Learning for Brain Tumor Segmentation with Missing ModalitiesCode1
Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analysesCode1
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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