SOTAVerified

Segmentation

Papers

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Showing 4251–4275 of 13072 papers

TitleStatusHype
All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenes—0
Acquisition-invariant brain MRI segmentation with informative uncertainties—0
Automatic CT Segmentation from Bounding Box Annotations using Convolutional Neural Networks—0
Flip Learning: Weakly Supervised Erase to Segment Nodules in Breast Ultrasound—0
Automatic Color Image Segmentation Using a Square Elemental Region-Based Seeded Region Growing and Merging Method—0
Deep Active Contours Using Locally Controlled Distance Vector Flow—0
Automatic Classification of Symmetry of Hemithoraces in Canine and Feline Radiographs—0
Decoupling Shape and Density for Liver Lesion Synthesis Using Conditional Generative Adversarial Networks—0
Automatic classification of geologic units in seismic images using partially interpreted examples—0
Automatic Cerebral Vessel Extraction in TOF-MRA Using Deep Learning—0
Computing Valid p-values for Image Segmentation by Selective Inference—0
Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation—0
All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentation—0
Flip Learning: Erase to Segment—0
Flow Based Self-supervised Pixel Embedding for Image Segmentation—0
Flow-guided Semi-supervised Video Object Segmentation—0
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images—0
Automatic Breast Ultrasound Image Segmentation: A Survey—0
Decoupled Motion Expression Video Segmentation—0
Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction—0
Acoustic Data-Driven Subword Modeling for End-to-End Speech Recognition—0
FLDNet: A Foreground-Aware Network for Polyp Segmentation Leveraging Long-Distance Dependencies—0
ALiSNet: Accurate and Lightweight Human Segmentation Network for Fashion E-Commerce—0
Deconvolutional Feature Stacking for Weakly-Supervised Semantic Segmentation—0
Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation—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