SOTAVerified

Segmentation

Papers

Showing 951975 of 13072 papers

TitleStatusHype
Adaptive Early-Learning Correction for Segmentation from Noisy AnnotationsCode1
CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray imagesCode1
3D Vascular Segmentation Supervised by 2D Annotation of Maximum Intensity ProjectionCode1
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray SegmentationCode1
3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce RegimesCode1
An attention-based U-Net for detecting deforestation within satellite sensor imageryCode1
Choroidalyzer: An open-source, end-to-end pipeline for choroidal analysis in optical coherence tomographyCode1
An Auto-Encoder Strategy for Adaptive Image SegmentationCode1
CiT-Net: Convolutional Neural Networks Hand in Hand with Vision Transformers for Medical Image SegmentationCode1
Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and SegmentationCode1
Evidential fully convolutional network for semantic segmentationCode1
Evidential segmentation of 3D PET/CT imagesCode1
3D Weakly Supervised Semantic Segmentation with 2D Vision-Language GuidanceCode1
Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and SegmentationCode1
ClaSP - Time Series SegmentationCode1
ClaSP -- Parameter-free Time Series SegmentationCode1
Classification Calibration for Long-tail Instance SegmentationCode1
ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised LearningCode1
Exploring Cross-Image Pixel Contrast for Semantic SegmentationCode1
Class-Balanced Pixel-Level Self-Labeling for Domain Adaptive Semantic SegmentationCode1
Detection-segmentation convolutional neural network for autonomous vehicle perceptionCode1
Exploring Deeper! Segment Anything Model with Depth Perception for Camouflaged Object DetectionCode1
Class-Incremental Learning for Semantic Segmentation Re-Using Neither Old Data Nor Old LabelsCode1
Class-incremental Continual Learning for Instance Segmentation with Image-level Weak SupervisionCode1
DEU-Net: Dual-Encoder U-Net for Automated Skin Lesion SegmentationCode1
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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