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Segmentation

Papers

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Showing 4701–4725 of 13072 papers

TitleStatusHype
Team Samsung-RAL: Technical Report for 2024 RoboDrive Challenge-Robust Map Segmentation Track—0
Simultaneous Deep Learning of Myocardium Segmentation and T2 Quantification for Acute Myocardial Infarction MRI—0
HARIS: Human-Like Attention for Reference Image Segmentation—0
Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge—0
Fourier Boundary Features Network with Wider Catchers for Glass Segmentation—0
CTS: A Consistency-Based Medical Image Segmentation ModelCode0
UDA4Inst: Unsupervised Domain Adaptation for Instance Segmentation—0
Shape-aware synthesis of pathological lung CT scans using CycleGAN for enhanced semi-supervised lung segmentationCode0
Automatic Segmentation of the Kidneys and Cystic Renal Lesions on Non-Contrast CT Using a Convolutional Neural Network—0
Rethinking Scanning Strategies with Vision Mamba in Semantic Segmentation of Remote Sensing Imagery: An Experimental Study—0
CLIP with Quality Captions: A Strong Pretraining for Vision Tasks—0
Adaptation of Distinct Semantics for Uncertain Areas in Polyp SegmentationCode0
CVAE-SM: A Conditional Variational Autoencoder with Style Modulation for Efficient Uncertainty QuantificationCode0
Investigating the Semantic Robustness of CLIP-based Zero-Shot Anomaly Segmentation—0
Leveraging Fixed and Dynamic Pseudo-labels for Semi-supervised Medical Image Segmentation—0
Meta-Learned Modality-Weighted Knowledge Distillation for Robust Multi-Modal Learning with Missing DataCode0
Brain MRI detection by Sematic Segmentation models- Transfer Learning approach—0
Global Motion Understanding in Large-Scale Video Object Segmentation—0
ODC-SA Net: Orthogonal Direction Enhancement and Scale Aware Network for Polyp Segmentation—0
Automated Cell Structure Extraction for 3D Electron Microscopy by Deep Learning—0
Prior-guided Diffusion Model for Cell Segmentation in Quantitative Phase Imaging—0
Multi-Target Unsupervised Domain Adaptation for Semantic Segmentation without External DataCode0
PCLMix: Weakly Supervised Medical Image Segmentation via Pixel-Level Contrastive Learning and Dynamic Mix AugmentationCode0
Enhancing Weakly Supervised Semantic Segmentation with Multi-modal Foundation Models: An End-to-End Approach—0
MDNet: Multi-Decoder Network for Abdominal CT Organs 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