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Semantic Segmentation

Papers

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Showing 9151–9200 of 14763 papers

TitleStatusHype
Meta-Learning via Learning with Distributed Memory—0
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation—0
MetaMorphosis: Task-oriented Privacy Cognizant Feature Generation for Multi-task Learning—0
Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning—0
MetaSeg: Content-Aware Meta-Net for Omni-Supervised Semantic Segmentation—0
Meta Segmentation Network for Ultra-Resolution Medical Images—0
MetaSegNet: Metadata-collaborative Vision-Language Representation Learning for Semantic Segmentation of Remote Sensing Images—0
Method of detecting the defects of the end face of steel coils—0
Machine Learning Pipeline for Segmentation and Defect Identification from High Resolution Transmission Electron Microscopy Data—0
Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art—0
M-FasterSeg: An Efficient Semantic Segmentation Network Based on Neural Architecture Search—0
MFNet: Multi-class Few-shot Segmentation Network with Pixel-wise Metric Learning—0
MFNet: Towards real-time semantic segmentation for autonomous vehicles with multi-spectral scenes—0
MFPNet: Multi-scale Feature Propagation Network For Lightweight Semantic Segmentation—0
A Novel Deep Learning Based Approach for Left Ventricle Segmentation in Echocardiography: MFP-Unet—0
MFSeg: Efficient Multi-frame 3D Semantic Segmentation—0
MGFI-Net: A Multi-Grained Feature Integration Network for Enhanced Medical Image Segmentation—0
MGTUNet: An new UNet for colon nuclei instance segmentation and quantification—0
MICDrop: Masking Image and Depth Features via Complementary Dropout for Domain-Adaptive Semantic Segmentation—0
Micro-Net: A unified model for segmentation of various objects in microscopy images—0
Microplastic Identification Using AI-Driven Image Segmentation and GAN-Generated Ecological Context—0
Microscopy Image Dataset for Deep Learning-Based Quantitative Assessment of Pulmonary Vascular Changes—0
Microvasculature Segmentation in Human BioMolecular Atlas Program (HuBMAP)—0
MILAN: Milli-Annotations for Lidar Semantic Segmentation—0
MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation—0
MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images—0
Mind The Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation—0
Minimal Adversarial Examples for Deep Learning on 3D Point Clouds—0
Minimax Active Learning—0
Minimizing Energy Costs in Deep Learning Model Training: The Gaussian Sampling Approach—0
Minimizing Labeled, Maximizing Unlabeled: An Image-Driven Approach for Video Instance Segmentation—0
Minimum Class Confusion based Transfer for Land Cover Segmentation in Rural and Urban Regions—0
MiniNet: An extremely lightweight convolutional neural network for real-time unsupervised monocular depth estimation—0
Mining of Single-Class by Active Learning for Semantic Segmentation—0
MIPR:Automatic Annotation of Medical Images with Pixel Rearrangement—0
MIRAM: Masked Image Reconstruction Across Multiple Scales for Breast Lesion Risk Prediction—0
MirrorNet: Bio-Inspired Camouflaged Object Segmentation—0
Mirror U-Net: Marrying Multimodal Fission with Multi-task Learning for Semantic Segmentation in Medical Imaging—0
Mirror-Yolo: A Novel Attention Focus, Instance Segmentation and Mirror Detection Model—0
Miss Detection vs. False Alarm: Adversarial Learning for Small Object Segmentation in Infrared Images—0
MISS: Memory-efficient Instance Segmentation Framework By Visual Inductive Priors Flow Propagation—0
MiSuRe is all you need to explain your image segmentation—0
Mitigating Attacks on Artificial Intelligence-based Spectrum Sensing for Cellular Network Signals—0
Mitigating Distributional Shift in Semantic Segmentation via Uncertainty Estimation from Unlabelled Data—0
Mitigating False Predictions In Unreasonable Body Regions—0
Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals—0
Mitigating the Impact of Attribute Editing on Face Recognition—0
Mitigating Undisciplined Over-Smoothing in Transformer for Weakly Supervised Semantic Segmentation—0
Mix and match networks: cross-modal alignment for zero-pair image-to-image translation—0
Mix-and-Match Tuning for Self-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
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