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Semantic Segmentation

Papers

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Showing 11501–11550 of 14763 papers

TitleStatusHype
Training-Free Robust Interactive Video Object Segmentation—0
Training-Free Semantic Segmentation via LLM-Supervision—0
Training Group Orthogonal Neural Networks with Privileged Information—0
Training Multi-organ Segmentation Networks with Sample Selection by Relaxed Upper Confident Bound—0
Training Object Detectors From Scratch: An Empirical Study in the Era of Vision Transformer—0
Training Semantic Segmentation on Heterogeneous Datasets—0
Training Structured Prediction Energy Networks with Indirect Supervision—0
Train, Learn, Expand, Repeat—0
Traits & Transferability of Adversarial Examples against Instance Segmentation & Object Detection—0
Transfer Learning of Semantic Segmentation Methods for Identifying Buried Archaeological Structures on LiDAR Data—0
Trans2Unet: Neural fusion for Nuclei Semantic Segmentation—0
TransAdapt: A Transformative Framework for Online Test Time Adaptive Semantic Segmentation—0
TransCC: Transformer Network for Coronary Artery CCTA Segmentation—0
TransCut: Transparent Object Segmentation from a Light-Field Image—0
TransDAE: Dual Attention Mechanism in a Hierarchical Transformer for Efficient Medical Image Segmentation—0
Transductive image segmentation: Self-training and effect of uncertainty estimation—0
TranSegPGD: Improving Transferability of Adversarial Examples on Semantic Segmentation—0
Transesophageal Echocardiography Generation using Anatomical Models—0
Transferability Estimation for Semantic Segmentation Task—0
Transferability Estimation using Bhattacharyya Class Separability—0
Transferability limitations for Covid 3D Localization Using SARS-CoV-2 segmentation models in 4D CT images—0
Transferability Metrics for Selecting Source Model Ensembles—0
Transferable Semi-supervised Semantic Segmentation—0
Brain MRI Tumor Segmentation with Adversarial Networks—0
Transfer Learning for Brain Tumor Segmentation—0
Transfer Learning for Instance Segmentation of Waste Bottles using Mask R-CNN Algorithm—0
Transfer Learning from Partial Annotations for Whole Brain Segmentation—0
Transfer Learning from Synthetic In-vitro Soybean Pods Dataset for In-situ Segmentation of On-branch Soybean Pod—0
Transferring and Regularizing Prediction for Semantic Segmentation—0
Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation—0
Transferring Knowledge for Food Image Segmentation using Transformers and Convolutions—0
Transferring learned patterns from ground-based field imagery to predict UAV-based imagery for crop and weed semantic segmentation in precision crop farming—0
Transferring Styles for Reduced Texture Bias and Improved Robustness in Semantic Segmentation Networks—0
Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging—0
Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation—0
Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation—0
Transformer-based Flood Scene Segmentation for Developing Countries—0
Transformer-CNN Cohort: Semi-supervised Semantic Segmentation by the Best of Both Students—0
Transformer-CNN Fused Architecture for Enhanced Skin Lesion Segmentation—0
Transformer Scale Gate for Semantic Segmentation—0
Transformers Meet Visual Learning Understanding: A Comprehensive Review—0
Transformer-Unet: Raw Image Processing with Unet—0
Transformer Utilization in Medical Image Segmentation Networks—0
Transforming Heart Chamber Imaging: Self-Supervised Learning for Whole Heart Reconstruction and Segmentation—0
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives—0
Transframer: Arbitrary Frame Prediction with Generative Models—0
TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers—0
TranSiam: Fusing Multimodal Visual Features Using Transformer for Medical Image Segmentation—0
Transitive Distance Clustering with K-Means Duality—0
TransLandSeg: A Transfer Learning Approach for Landslide Semantic Segmentation Based on Vision Foundation Model—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