SOTAVerified

Segmentation

Papers

Showing 901925 of 13072 papers

TitleStatusHype
Anabranch Network for Camouflaged Object SegmentationCode1
DoubleU-Net: A Deep Convolutional Neural Network for Medical Image SegmentationCode1
Conditional Convolutions for Instance SegmentationCode1
An Accelerated Pipeline for Multi-label Renal Pathology Image Segmentation at the Whole Slide Image LevelCode1
Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal DistillationCode1
DropLoss for Long-Tail Instance SegmentationCode1
3D Tooth Mesh Segmentation with Simplified Mesh Cell RepresentationCode1
DRU-net: An Efficient Deep Convolutional Neural Network for Medical Image SegmentationCode1
Event-Free Moving Object Segmentation from Moving Ego VehicleCode1
Beyond Pixels: Enhancing LIME with Hierarchical Features and Segmentation Foundation ModelsCode1
CondNet: Conditional Classifier for Scene SegmentationCode1
Context-aware Feature Generation for Zero-shot Semantic SegmentationCode1
Dual Multi-scale Mean Teacher Network for Semi-supervised Infection Segmentation in Chest CT Volume for COVID-19Code1
CateNorm: Categorical Normalization for Robust Medical Image SegmentationCode1
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object SegmentationCode1
Dual Super-Resolution Learning for Semantic SegmentationCode1
DuAT: Dual-Aggregation Transformer Network for Medical Image SegmentationCode1
Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image SegmentationCode1
Continuous Conditional Random Field Convolution for Point Cloud SegmentationCode1
CPP-Net: Context-aware Polygon Proposal Network for Nucleus SegmentationCode1
Dynamic Gradient Sparsification Training for Few-Shot Fine-tuning of CT Lymph Node Segmentation Foundation ModelCode1
Dynamic Neural Representational Decoders for High-Resolution Semantic SegmentationCode1
Comprehensive segmentation of deep grey nuclei from structural MRI dataCode1
Dynamic Token Pruning in Plain Vision Transformers for Semantic SegmentationCode1
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