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Semantic Segmentation

Papers

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Showing 6576–6600 of 14763 papers

TitleStatusHype
Confidence Estimation via Auxiliary Models—0
A State-of-the-art Survey of U-Net in Microscopic Image Analysis: from Simple Usage to Structure Mortification—0
Improved Inference via Deep Input Transfer—0
(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network—0
Improved-Mask R-CNN: Towards an Accurate Generic MSK MRI instance segmentation platform (Data from the Osteoarthritis Initiative)—0
Improved Noise and Attack Robustness for Semantic Segmentation by Using Multi-Task Training with Self-Supervised Depth Estimation—0
DArch: Dental Arch Prior-assisted 3D Tooth Instance Segmentation—0
A Classifier-Free Incremental Learning Framework for Scalable Medical Image Segmentation—0
Improved Training for Self-Training by Confidence Assessments—0
Improved Unet brain tumor image segmentation based on GSConv module and ECA attention mechanism—0
Improved Unet model for brain tumor image segmentation based on ASPP-coordinate attention mechanism—0
Improved Workflow for Unsupervised Multiphase Image Segmentation—0
Improvement of Multiparametric MR Image Segmentation by Augmenting the Data with Generative Adversarial Networks for Glioma Patients—0
Improve Supervised Representation Learning with Masked Image Modeling—0
Fully Convolutional Neural Networks for Raw Eye Tracking Data Segmentation, Generation, and Reconstruction—0
Confidence Calibration for Object Detection and Segmentation—0
Improving 2D Feature Representations by 3D-Aware Fine-Tuning—0
Improving 3D Occupancy Prediction through Class-balancing Loss and Multi-scale Representation—0
LangSurf: Language-Embedded Surface Gaussians for 3D Scene Understanding—0
Fully Convolutional Neural Networks for Crowd Segmentation—0
Fully Convolutional Neural Network for Semantic Segmentation of Anatomical Structure and Pathologies in Colour Fundus Images Associated with Diabetic Retinopathy—0
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation—0
DaSeGAN: Domain Adaptation for Segmentation Tasks via Generative Adversarial Networks—0
Fully Convolutional Networks with Sequential Information for Robust Crop and Weed Detection in Precision Farming—0
Fully Convolutional Neural Networks to Detect Clinical Dermoscopic Features—0
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All datasetsADE20KNYU-Depth V2Cityscapes testCityscapes valADE20K valPASCAL ContextS3DIS Area5PASCAL VOC 2012 testS3DISScanNetSUN-RGBDDensePASS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310—Unverified
2ViT-P (InternImage-H)Validation mIoU63.6—Unverified
3ONE-PEACEValidation mIoU63—Unverified
4M3I Pre-training (InternImage-H)Validation mIoU62.9—Unverified
5InternImage-HValidation mIoU62.9—Unverified
6BEiT-3Validation mIoU62.8—Unverified
7EVAValidation mIoU62.3—Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6—Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5—Unverified
10FD-SwinV2-GValidation mIoU61.4—Unverified