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Semantic Segmentation

Papers

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Showing 7251–7275 of 14763 papers

TitleStatusHype
L-MAE: Masked Autoencoders are Semantic Segmentation Datasets Augmenter—0
Deep Multiphase Level Set for Scene Parsing—0
Labeling Where Adapting Fails: Cross-Domain Semantic Segmentation with Point Supervision via Active Selection—0
Labeling Panoramas with Spherical Hourglass Networks—0
Deep Multimodal Fusion for Semantic Segmentation of Remote Sensing Earth Observation Data—0
Bayesian nonparametric image segmentation using a generalized Swendsen-Wang algorithm—0
Labeling Indoor Scenes with Fusion of Out-of-the-Box Perception Models—0
Language-driven Grasp Detection with Mask-guided Attention—0
Deep Multi-Magnification Networks for Multi-Class Breast Cancer Image Segmentation—0
Bayesian Neural Networks for Uncertainty Estimation of Imaging Biomarkers—0
Label-free Neural Semantic Image Synthesis—0
Label Filling via Mixed Supervision for Medical Image Segmentation from Noisy Annotations—0
Deep Multi Label Classification in Affine Subspaces—0
Deep Multi-Branch Aggregation Network for Real-Time Semantic Segmentation in Street Scenes—0
Language-Guided Instance-Aware Domain-Adaptive Panoptic Segmentation—0
Language-guided Medical Image Segmentation with Target-informed Multi-level Contrastive Alignments—0
Language-Mediated, Object-Centric Representation Learning—0
Bayesian Multifractal Image Segmentation—0
Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach—0
Label-Efficient LiDAR Semantic Segmentation with 2D-3D Vision Transformer Adapters—0
DeepMRSeg: A convolutional deep neural network for anatomy and abnormality segmentation on MR images—0
Bayesian Logistic Shape Model Inference: application to cochlea image segmentation—0
Amodal Instance Segmentation—0
ACT: Semi-supervised Domain-adaptive Medical Image Segmentation with Asymmetric Co-training—0
Label-Efficient LiDAR Panoptic 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