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Semantic Segmentation

Papers

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Showing 7951–8000 of 14763 papers

TitleStatusHype
Deep Geodesic Learning for Segmentation and Anatomical Landmarking—0
Lung Segmentation in Chest X-rays with Res-CR-Net—0
A Local-Global Approach to Semantic Segmentation in Aerial Images—0
Introducing A Novel Method For Adaptive Thresholding In Brain Tumor Medical Image Segmentation—0
Deep Generative Model-based Quality Control for Cardiac MRI Segmentation—0
DeepGamble: Towards unlocking real-time player intelligence using multi-layer instance segmentation and attribute detection—0
A Local Active Contour Model for Image Segmentation with Intensity Inhomogeneity—0
Active Learning for Point Cloud Semantic Segmentation via Spatial-Structural Diversity Reasoning—0
INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation—0
In The Wild Ellipse Parameter Estimation for Circular Dining Plates and Bowls—0
In the Era of Prompt Learning with Vision-Language Models—0
Inter-slice image augmentation based on frame interpolation for boosting medical image segmentation accuracy—0
Deep FusionNet for Point Cloud Semantic Segmentation—0
A Vanilla Multi-Task Framework for Dense Visual Prediction Solution to 1st VCL Challenge -- Multi-Task Robustness Track—0
Inter-Scale Dependency Modeling for Skin Lesion Segmentation with Transformer-based Networks—0
Deep Free-Form Deformation Network for Object-Mask Registration—0
InterRVOS: Interaction-aware Referring Video Object Segmentation—0
DeepFracture: A Generative Approach for Predicting Brittle Fractures with Neural Discrete Representation Learning—0
AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving—0
Interpretable Small Training Set Image Segmentation Network Originated from Multi-Grid Variational Model—0
Interpretable and synergistic deep learning for visual explanation and statistical estimations of segmentation of disease features from medical images—0
Deep feature transfer between localization and segmentation tasks—0
Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation—0
M^33D: Learning 3D priors using Multi-Modal Masked Autoencoders for 2D image and video understanding—0
Deep feature selection-and-fusion for RGB-D semantic segmentation—0
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation—0
All You Need is LUV: Unsupervised Collection of Labeled Images using Invisible UV Fluorescent Indicators—0
TAM-VT: Transformation-Aware Multi-scale Video Transformer for Segmentation and Tracking—0
Internal-External Boundary Attention Fusion for Glass Surface Segmentation—0
Deepfake Image Generation for Improved Brain Tumor Segmentation—0
Interior point search for nonparametric image segmentation—0
DeepFake Detection Based on the Discrepancy Between the Face and its Context—0
Auxiliary Learning by Implicit Differentiation—0
Interclass Prototype Relation for Few-Shot Segmentation—0
Inter-BMV: Interpolation with Block Motion Vectors for Fast Semantic Segmentation on Video—0
MacFormer: Semantic Segmentation with Fine Object Boundaries—0
DeeperLab: Single-Shot Image Parser—0
Machine Learning-based Automatic Graphene Detection with Color Correction for Optical Microscope Images—0
Interactive Video Object Segmentation in the Wild—0
Deep ensembles in bioimage segmentation—0
AUTV: Creating Underwater Video Datasets with Pixel-wise Annotations—0
All You Need Is Boundary: Toward Arbitrary-Shaped Text Spotting—0
All you need is a second look: Towards Tighter Arbitrary shape text detection—0
3D Scene Parsing via Class-Wise Adaptation—0
MAELi: Masked Autoencoder for Large-Scale LiDAR Point Clouds—0
MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition—0
3DSceneEditor: Controllable 3D Scene Editing with Gaussian Splatting—0
SAGE: A Framework of Precise Retrieval for RAG—0
Interactive user interface based on Convolutional Auto-encoders for annotating CT-scans—0
Interactive Segmentation via Deep Learning and B-Spline Explicit Active Surfaces—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