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Semantic Segmentation

Papers

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Showing 6551–6600 of 14763 papers

TitleStatusHype
A Classifier-guided Approach for Top-down Salient Object Detection—0
Fully Transformer Networks for Semantic Image Segmentation—0
Fully Transformer-Equipped Architecture for End-to-End Referring Video Object Segmentation—0
Implicit Label Augmentation on Partially Annotated Clips via Temporally-Adaptive Features Learning—0
Implicit Modeling -- A Generalization of Discriminative and Generative Approaches—0
DaF-BEVSeg: Distortion-aware Fisheye Camera based Bird's Eye View Segmentation with Occlusion Reasoning—0
Confidence Intervals for Performance Estimates in Brain MRI Segmentation—0
Language-Assisted 3D Scene Understanding—0
DAG-Recurrent Neural Networks For Scene Labeling—0
Implicit Surface Contrastive Clustering for LiDAR Point Clouds—0
Implicit U-KAN2.0: Dynamic, Efficient and Interpretable Medical Image Segmentation—0
Implicit U-Net for volumetric medical image segmentation—0
Language-Based Depth Hints for Monocular Depth Estimation—0
Language-driven Grasp Detection with Mask-guided Attention—0
Importance-Aware Semantic Segmentation in Self-Driving with Discrete Wasserstein Training—0
Automatically Designing CNN Architectures for Medical Image Segmentation—0
Language-Guided Instance-Aware Domain-Adaptive Panoptic Segmentation—0
Confidence-Guided Unsupervised Domain Adaptation for Cerebellum Segmentation—0
Fully Self-Supervised Learning for Semantic Segmentation—0
Importance of Self-Consistency in Active Learning for Semantic Segmentation—0
DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference—0
Automatically Searching for U-Net Image Translator Architecture—0
Improved Block Merging for 3D Point Cloud Instance Segmentation—0
Improved Crop and Weed Detection with Diverse Data Ensemble Learning—0
Fully Hyperbolic Convolutional Neural Networks—0
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
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