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Semantic Segmentation

Papers

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Showing 8301–8350 of 14763 papers

TitleStatusHype
PLU-Net: Extraction of multi-scale feature fusion—0
Pixel Difference Convolutional Network for RGB-D Semantic Segmentation—0
Slim U-Net: Efficient Anatomical Feature Preserving U-net Architecture for Ultrasound Image Segmentation—0
DISCO: Distributed Inference with Sparse Communications—0
Evaluation of Extra Pixel Interpolation with Mask Processing for Medical Image Segmentation with Deep Learning—0
Effects of Architectures on Continual Semantic Segmentation—0
Few-Shot Point Cloud Semantic Segmentation via Contrastive Self-Supervision and Multi-Resolution Attention—0
Non-pooling Network for medical image segmentation—0
Semantic Segmentation of Urban Textured Meshes Through Point Sampling—0
Towards Simultaneous Segmentation of Liver Tumors and Intrahepatic Vessels via Cross-attention Mechanism—0
ENInst: Enhancing Weakly-supervised Low-shot Instance Segmentation—0
Hadamard Layer to Improve Semantic Segmentation—0
A Survey on Semi-Supervised Semantic Segmentation—0
TAX: Tendency-and-Assignment Explainer for Semantic Segmentation with Multi-Annotators—0
SEMI-PointRend: Improved Semiconductor Wafer Defect Classification and Segmentation as Rendering—0
Redes Generativas Adversarias (GAN) Fundamentos Teóricos y Aplicaciones—0
Model Doctor for Diagnosing and Treating Segmentation ErrorCode0
Few-shot 3D LiDAR Semantic Segmentation for Autonomous Driving—0
Local-to-Global Information Communication for Real-Time Semantic Segmentation Network Search—0
Frequency-domain Learning for Volumetric-based 3D Data Perception—0
Navya3DSeg -- Navya 3D Semantic Segmentation Dataset & split generation for autonomous vehicles—0
TransUPR: A Transformer-based Uncertain Point Refiner for LiDAR Point Cloud Semantic Segmentation—0
Offline-to-Online Knowledge Distillation for Video Instance Segmentation—0
Self-supervised Registration and Segmentation of the Ossicles with A Single Ground Truth Label—0
TFormer: A Transmission-Friendly ViT Model for IoT Devices—0
Optimal Transport for Change Detection on LiDAR Point CloudsCode0
Semantic Image Segmentation: Two Decades of Research—0
RFC-Net: Learning High Resolution Global Features for Medical Image Segmentation on a Computational Budget—0
PUPS: Point Cloud Unified Panoptic Segmentation—0
A Deep Learning-based Global and Segmentation-based Semantic Feature Fusion Approach for Indoor Scene Classification—0
A Neuromorphic Dataset for Object Segmentation in Indoor Cluttered EnvironmentCode0
Between Generating Noise and Generating Images: Noise in the Correct Frequency Improves the Quality of Synthetic Histopathology Images for Digital Pathology—0
Self-supervised pseudo-colorizing of masked cellsCode0
Evaluation of Data Augmentation and Loss Functions in Semantic Image Segmentation for Drilling Tool Wear DetectionCode0
IH-ViT: Vision Transformer-based Integrated Circuit Appear-ance Defect Detection—0
Lithium Metal Battery Quality Control via Transformer-CNN Segmentation—0
Optimized Hybrid Focal Margin Loss for Crack Segmentation—0
Multi-Modal Evaluation Approach for Medical Image Segmentation—0
SwinCross: Cross-modal Swin Transformer for Head-and-Neck Tumor Segmentation in PET/CT Images—0
Best Practices in Active Learning for Semantic Segmentation—0
The XPRESS Challenge: Xray Projectomic Reconstruction -- Extracting Segmentation with Skeletons—0
A Generalized Surface Loss for Reducing the Hausdorff Distance in Medical Imaging SegmentationCode0
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning ConventionsCode0
An Efficient Instance Segmentation Approach for Extracting Fission Gas Bubbles on U-10Zr Annular Fuel—0
An End-to-End Two-Phase Deep Learning-Based workflow to Segment Man-made Objects Around Reservoirs—0
Improving CT Image Segmentation Accuracy Using StyleGAN Driven Data Augmentation—0
SimCon Loss with Multiple Views for Text Supervised Semantic Segmentation—0
SSR-2D: Semantic 3D Scene Reconstruction from 2D Images—0
Scaling Vision-based End-to-End Driving with Multi-View Attention Learning—0
Using t-distributed stochastic neighbor embedding for visualization and segmentation of 3D point clouds of plants—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
4InternImage-HValidation mIoU62.9—Unverified
5M3I Pre-training (InternImage-H)Validation 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