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Semantic Segmentation

Papers

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Showing 8926–8950 of 14763 papers

TitleStatusHype
A Novel Deep Learning Based Approach for Left Ventricle Segmentation in Echocardiography: MFP-Unet—0
MVMO: A Multi-Object Dataset for Wide Baseline Multi-View Semantic Segmentation—0
Training Semantic Segmentation on Heterogeneous Datasets—0
Training Structured Prediction Energy Networks with Indirect Supervision—0
MVFormer: Diversifying Feature Normalization and Token Mixing for Efficient Vision Transformers—0
Train, Learn, Expand, Repeat—0
MV-Adapter: Enhancing Underwater Instance Segmentation via Adaptive Channel Attention—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
WeatherProof: A Paired-Dataset Approach to Semantic Segmentation in Adverse Weather—0
MV6D: Multi-View 6D Pose Estimation on RGB-D Frames Using a Deep Point-wise Voting Network—0
MUVOD: A Novel Multi-view Video Object Segmentation Dataset and A Benchmark for 3D Segmentation—0
TransAdapt: A Transformative Framework for Online Test Time Adaptive Semantic Segmentation—0
MUVA: A New Large-Scale Benchmark for Multi-View Amodal Instance Segmentation in the Shopping Scenario—0
Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation—0
Mutual information deep regularization for semi-supervised segmentation—0
Mutual-GAN: Towards Unsupervised Cross-Weather Adaptation with Mutual Information Constraint—0
TransCC: Transformer Network for Coronary Artery CCTA Segmentation—0
WeatherProof: Leveraging Language Guidance for Semantic Segmentation in Adverse Weather—0
Mutual Evidential Deep Learning for Medical Image 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
Mutual- and Self- Prototype Alignment for Semi-supervised Medical Image Segmentation—0
MuSCLe: A Multi-Strategy Contrastive Learning Framework for Weakly Supervised Semantic Segmentation—0
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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