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Semantic Segmentation

Papers

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Showing 7476–7500 of 14763 papers

TitleStatusHype
A Metacognitive Approach to Out-of-Distribution Detection for Segmentation—0
Keep the Balance: A Parameter-Efficient Symmetrical Framework for RGB+X Semantic Segmentation—0
Learning Multiscale Consistency for Self-supervised Electron Microscopy Instance Segmentation—0
Deep Learning for Semantic Segmentation on Minimal Hardware—0
KCP: Kernel Cluster Pruning for Dense Labeling Neural Networks—0
Deep learning for semantic segmentation of remote sensing images with rich spectral content—0
KAN-Mamba FusionNet: Redefining Medical Image Segmentation with Non-Linear Modeling—0
KANDU-Net:A Dual-Channel U-Net with KAN for Medical Image Segmentation—0
Deep Learning for Semantic Part Segmentation with High-Level Guidance—0
Deep Learning for Ranking Response Surfaces with Applications to Optimal Stopping Problems—0
Active Testing: An Efficient and Robust Framework for Estimating Accuracy—0
Kaiwu: A Multimodal Manipulation Dataset and Framework for Robot Learning and Human-Robot Interaction—0
KA^2ER: Knowledge Adaptive Amalgamation of ExpeRts for Medical Images Segmentation—0
Just Say Better or Worse: A Human-AI Collaborative Framework for Medical Image Segmentation Without Manual Annotations—0
Deep Learning for Object Saliency Detection and Image Segmentation—0
Balancing Robustness and Efficiency in Embedded DNNs Through Activation Function Selection—0
Juggling With Representations: On the Information Transfer Between Imagery, Point Clouds, and Meshes for Multi-Modal Semantics—0
Learning Ordinality in Semantic Segmentation—0
JSSR: A Joint Synthesis, Segmentation, and Registration System for 3D Multi-Modal Image Alignment of Large-scale Pathological CT Scans—0
JSMNet Improving Indoor Point Cloud Semantic and Instance Segmentation through Self-Attention and Multiscale—0
Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities—0
Learning Personalized Modular Network Guided by Structured Knowledge—0
Balancing Multi-Target Semi-Supervised Medical Image Segmentation with Collaborative Generalist and Specialists—0
Learning Pixel Representations for Generic Segmentation—0
Joint Topology-Preserving and Feature-Refinement Network for Curvilinear Structure 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
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