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Semantic Segmentation

Papers

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Showing 7201–7250 of 14763 papers

TitleStatusHype
S4C: Self-Supervised Semantic Scene Completion with Neural Fields—0
Impact of Label Types on Training SWIN Models with Overhead Imagery—0
Heuristic Vision Pre-Training with Self-Supervised and Supervised Multi-Task Learning—0
Robust Unsupervised Domain Adaptation by Retaining Confident Entropy via Edge Concatenation—0
HaarNet: Large-scale Linear-Morphological Hybrid Network for RGB-D Semantic Segmentation—0
Context-Enhanced Detector For Building Detection From Remote Sensing Images—0
Line Detection and Segmentation of Annual Crops Using Hybrid MethodCode0
CLIP for Lightweight Semantic Segmentation—0
PeP: a Point enhanced Painting method for unified point cloud tasks—0
Self-supervised Object-Centric Learning for Videos—0
Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real ImagesCode0
Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models—0
ViTs are Everywhere: A Comprehensive Study Showcasing Vision Transformers in Different Domain—0
From Question to Exploration: Test-Time Adaptation in Semantic Segmentation?Code0
SimPLR: A Simple and Plain Transformer for Scaling-Efficient Object Detection and Segmentation—0
Hierarchical Side-Tuning for Vision Transformers—0
Unleashing the power of Neural Collapse for Transferability Estimation—0
CoBEVFusion: Cooperative Perception with LiDAR-Camera Bird's-Eye View Fusion—0
Empirical Evaluation of the Segment Anything Model (SAM) for Brain Tumor Segmentation—0
WinSyn: A High Resolution Testbed for Synthetic DataCode0
Bidirectional Knowledge Reconfiguration for Lightweight Point Cloud Analysis—0
Detecting Abnormal Health Conditions in Smart Home Using a Drone—0
Cross-Task Data Augmentation by Pseudo-label Generation for Region Based Coronary Artery Instance Segmentation—0
Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy—0
Geometry Aware Field-to-field Transformations for 3D Semantic Segmentation—0
Enhancing Representations through Heterogeneous Self-Supervised Learning—0
SemST: Semantically Consistent Multi-Scale Image Translation via Structure-Texture Alignment—0
Structure-Preserving Instance Segmentation via Skeleton-Aware Distance Transform—0
Towards Dynamic and Small Objects Refinement for Unsupervised Domain Adaptative Nighttime Semantic Segmentation—0
Activate and Reject: Towards Safe Domain Generalization under Category Shift—0
ConvNeXtv2 Fusion with Mask R-CNN for Automatic Region Based Coronary Artery Stenosis Detection for Disease DiagnosisCode0
AG-CRC: Anatomy-Guided Colorectal Cancer Segmentation in CT with Imperfect Anatomical KnowledgeCode0
Combining UPerNet and ConvNeXt for Contrails Identification to reduce Global WarmingCode0
Federated Self-Supervised Learning of Monocular Depth Estimators for Autonomous Vehicles—0
Memory-Constrained Semantic Segmentation for Ultra-High Resolution UAV Imagery—0
TransCC: Transformer Network for Coronary Artery CCTA Segmentation—0
DiffPrompter: Differentiable Implicit Visual Prompts for Semantic-Segmentation in Adverse Conditions—0
CUPre: Cross-domain Unsupervised Pre-training for Few-Shot Cell Segmentation—0
Semantic segmentation of longitudinal thermal images for identification of hot and cool spots in urban areas—0
Tool Wear Segmentation in Blanking Processes with Fully Convolutional Networks based Digital Image Processing—0
Sub-token ViT Embedding via Stochastic Resonance TransformersCode0
A Deeply Supervised Semantic Segmentation Method Based on GAN—0
Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptation—0
Ammonia-Net: A Multi-task Joint Learning Model for Multi-class Segmentation and Classification in Tooth-marked Tongue Diagnosis—0
AI-based automated active learning for discovery of hidden dynamic processes: A use case in light microscopy—0
HartleyMHA: Self-Attention in Frequency Domain for Resolution-Robust and Parameter-Efficient 3D Image Segmentation—0
FNOSeg3D: Resolution-Robust 3D Image Segmentation with Fourier Neural Operator—0
Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification—0
Exploring DINO: Emergent Properties and Limitations for Synthetic Aperture Radar Imagery—0
Ablation Study to Clarify the Mechanism of Object Segmentation in Multi-Object Representation Learning—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