SOTAVerified

Segmentation

Papers

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Showing 6851–6900 of 13072 papers

TitleStatusHype
Measures and Meta-Measures for the Supervised Evaluation of Image Segmentation—0
Lesion Conditional Image Generation for Improved Segmentation of Intracranial Hemorrhage from CT Images—0
Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning—0
Deep Learning Methods for Lung Cancer Segmentation in Whole-slide Histopathology Images -- the ACDC@LungHP Challenge 2019—0
Lesion Net -- Skin Lesion Segmentation Using Coordinate Convolution and Deep Residual Units—0
Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection—0
Lesion Segmentation in Whole-Body Multi-Tracer PET-CT Images; a Contribution to AutoPET 2024 Challenge—0
Lesion segmentation using U-Net network—0
FoodMem: Near Real-time and Precise Food Video Segmentation—0
LesionSeg: Semantic segmentation of skin lesions using Deep Convolutional Neural Network—0
FoodLMM: A Versatile Food Assistant using Large Multi-modal Model—0
FOMTrace: Interactive Video Segmentation By Image Graphs and Fuzzy Object Models—0
FODVid: Flow-guided Object Discovery in Videos—0
Less is More: Unsupervised Mask-guided Annotated CT Image Synthesis with Minimum Manual Segmentations—0
Focus, Segment and Erase: An Efficient Network for Multi-Label Brain Tumor Segmentation—0
LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds—0
LEST: Large-scale LiDAR Semantic Segmentation with Transformer—0
Let Human Sketches Help: Empowering Challenging Image Segmentation Task with Freehand Sketches—0
Deep-learning Segmentation of Small Volumes in CT images for Radiotherapy Treatment Planning—0
Class-wise Dynamic Graph Convolution for Semantic Segmentation—0
Level Set KSVD—0
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation—0
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation—0
Leverage Cross-Attention for End-to-End Open-Vocabulary Panoptic Reconstruction—0
Leverage Weakly Annotation to Pixel-wise Annotation via Zero-shot Segment Anything Model for Molecular-empowered Learning—0
Leveraging 3D Information in Unsupervised Brain MRI Segmentation—0
Leveraging Adaptive Implicit Representation Mapping for Ultra High-Resolution Image Segmentation—0
Leveraging Anatomical Constraints with Uncertainty for Pneumothorax Segmentation—0
A Regularized Convolutional Neural Network for Semantic Image Segmentation—0
Leveraging Auxiliary Classification for Rib Fracture Segmentation—0
A Region of Interest Focused Triple UNet Architecture for Skin Lesion Segmentation—0
Deep Learning with Mixed Supervision for Brain Tumor Segmentation—0
Leveraging Clinical Characteristics for Improved Deep Learning-Based Kidney Tumor Segmentation on CT—0
Leveraging Contrastive Learning for Semantic Segmentation with Consistent Labels Across Varying Appearances—0
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans—0
Leveraging Fixed and Dynamic Pseudo-labels for Semi-supervised Medical Image Segmentation—0
MDFI-Net: Multiscale Differential Feature Interaction Network for Accurate Retinal Vessel Segmentation—0
Leveraging Frequency Domain Learning in 3D Vessel Segmentation—0
Deeply Self-Supervised Contour Embedded Neural Network Applied to Liver Segmentation—0
Leveraging Global Binary Masks for Structure Segmentation in Medical Images—0
FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images—0
Leveraging Image Complexity in Macro-Level Neural Network Design for Medical Image Segmentation—0
Leveraging in-domain supervision for unsupervised image-to-image translation tasks via multi-stream generators—0
Classroom Slide Narration System—0
A recurrent connectionist model of melody perception : An exploration using TRACX2—0
MDNet: Multi-Decoder Network for Abdominal CT Organs Segmentation—0
Leveraging Large-Scale Pretrained Vision Foundation Models for Label-Efficient 3D Point Cloud Segmentation—0
Automatic Segmentation of the Left Ventricle in Cardiac CT Angiography Using Convolutional Neural Network—0
Class-level Multiple Distributions Representation are Necessary for Semantic Segmentation—0
Adversarial Learning with Multiscale Features and Kernel Factorization for Retinal Blood Vessel Segmentation—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