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Semantic Segmentation

Papers

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Showing 8001–8050 of 14763 papers

TitleStatusHype
Differentiable Sensor Layouts for End-to-End Learning of Task-Specific Camera Parameters—0
DIAMANT: Dual Image-Attention Map Encoders For Medical Image Segmentation—0
Quality-Adaptive Split-Federated Learning for Segmenting Medical Images with Inaccurate Annotations—0
SCOPE: Structural Continuity Preservation for Medical Image Segmentation—0
SAM Meets Robotic Surgery: An Empirical Study in Robustness Perspective—0
SAM on Medical Images: A Comprehensive Study on Three Prompt Modes—0
Multi-to-Single Knowledge Distillation for Point Cloud Semantic SegmentationCode0
Neural Implicit Dense Semantic SLAM—0
SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model—0
Human Semantic Segmentation using Millimeter-Wave Radar Sparse Point Clouds—0
Dual-feature Fusion Attention Network for Small Object Segmentation—0
FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation—0
Compensation Learning in Semantic SegmentationCode0
Cluster Entropy: Active Domain Adaptation in Pathological Image Segmentation—0
Exploiting CNNs for Semantic Segmentation with Pascal VOC—0
Mixing Data Augmentation with Preserving Foreground Regions in Medical Image Segmentation—0
Self-Supervised Temporal Analysis of Spatiotemporal Data—0
The Potential of Visual ChatGPT For Remote Sensing—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
Segment anything, from space?—0
STM-UNet: An Efficient U-shaped Architecture Based on Swin Transformer and Multi-scale MLP for Medical Image Segmentation—0
Topology-Aware Focal Loss for 3D Image Segmentation—0
Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving—0
Augmentation-based Domain Generalization for Semantic Segmentation—0
Accurate and Efficient Event-based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Network—0
Robust and Efficient Memory Network for Video Object Segmentation—0
Semi-Supervised Semantic Segmentation With Region RelevanceCode0
Segment Anything in Non-Euclidean Domains: Challenges and Opportunities—0
Dilated-UNet: A Fast and Accurate Medical Image Segmentation Approach using a Dilated Transformer and U-Net ArchitectureCode0
Incomplete Multimodal Learning for Remote Sensing Data Fusion—0
SACANet: scene-aware class attention network for semantic segmentation of remote sensing images—0
SSS3D: Fast Neural Architecture Search For Efficient Three-Dimensional Semantic Segmentation—0
Deep Attention Unet: A Network Model with Global Feature Perception Ability—0
A Preliminary Study of Deep Learning Sensor Fusion for Pedestrian DetectionCode0
Ensembling Instance and Semantic Segmentation for Panoptic Segmentation—0
Securing Neural Networks with Knapsack OptimizationCode0
Boosting Semantic Segmentation with Semantic BoundariesCode0
Learning Temporal Distribution and Spatial Correlation Towards Universal Moving Object SegmentationCode0
Baybayin Character Instance Detection—0
DCELANM-Net:Medical Image Segmentation based on Dual Channel Efficient Layer Aggregation Network with Learner—0
Few-shot Medical Image Segmentation via Cross-Reference Transformer—0
Realistic Data Enrichment for Robust Image Segmentation in Histopathology—0
Motion-state Alignment for Video Semantic Segmentation—0
UDTIRI: An Online Open-Source Intelligent Road Inspection Benchmark Suite—0
Coupling Global Context and Local Contents for Weakly-Supervised Semantic SegmentationCode0
Perceive, Excavate and Purify: A Novel Object Mining Framework for Instance Segmentation—0
Computer-Vision Benchmark Segment-Anything Model (SAM) in Medical Images: Accuracy in 12 Datasets—0
Dual Stage Stylization Modulation for Domain Generalized Semantic Segmentation—0
Learning to "Segment Anything" in Thermal Infrared Images through Knowledge Distillation with a Large Scale Dataset SATIRCode0
When SAM Meets Medical Images: An Investigation of Segment Anything Model (SAM) on Multi-phase Liver Tumor Segmentation—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
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