SOTAVerified

Segmentation

Papers

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Showing 4126–4150 of 13072 papers

TitleStatusHype
Deep learning architectures for automated image segmentation—0
A Mask Attention Interaction and Scale Enhancement Network for SAR Ship Instance Segmentation—0
Deep learning approaches to surgical video segmentation and object detection: A Scoping Review—0
Deep learning and its application to medical image segmentation—0
Automatic Lumbar Spinal CT Image Segmentation with a Dual Densely Connected U-Net—0
3D Segmentation of Humans in Point Clouds with Synthetic Data—0
Automatic lobe segmentation using attentive cross entropy and end-to-end fissure generation—0
Deep Label Fusion: A 3D End-to-End Hybrid Multi-Atlas Segmentation and Deep Learning Pipeline—0
AMA-SAM: Adversarial Multi-Domain Alignment of Segment Anything Model for High-Fidelity Histology Nuclei Segmentation—0
DeepIrisNet2: Learning Deep-IrisCodes from Scratch for Segmentation-Robust Visible Wavelength and Near Infrared Iris Recognition—0
Deep Interactive Region Segmentation and Captioning—0
Automatic Liver Segmentation with Adversarial Loss and Convolutional Neural Network—0
Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation—0
Automatic Liver Segmentation Using an Adversarial Image-to-Image Network—0
Deep Instance Segmentation with Automotive Radar Detection Points—0
A Markov Random Field and Active Contour Image Segmentation Model for Animal Spots Patterns—0
Action parsing using context features—0
VINCIE: Unlocking In-context Image Editing from Video—0
Federated Semi-supervised Learning for Medical Image Segmentation with intra-client and inter-client Consistency—0
DeepHIPS: A novel Deep Learning based Hippocampus Subfield Segmentation method—0
Automatic Liver Lesion Segmentation Using A Deep Convolutional Neural Network Method—0
Deep Hierarchical Parsing for Semantic Segmentation—0
Automatic Liver Lesion Detection using Cascaded Deep Residual Networks—0
A margin-based replacement for cross-entropy loss—0
Deep Grouping Model for Unified Perceptual Parsing—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