SOTAVerified

Semantic Segmentation

Papers

Showing 676700 of 14763 papers

TitleStatusHype
MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated DatasetCode2
CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image FusionCode2
MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image SegmentationCode2
4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural NetworksCode2
ARKit LabelMaker: A New Scale for Indoor 3D Scene UnderstandingCode2
Modeling the Label Distributions for Weakly-Supervised Semantic SegmentationCode2
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using SparsityCode2
Cross Language Image Matching for Weakly Supervised Semantic SegmentationCode2
Moving Object Segmentation in Point Cloud Data using Hidden Markov ModelsCode2
Customized Segment Anything Model for Medical Image SegmentationCode2
MSVM-UNet: Multi-Scale Vision Mamba UNet for Medical Image SegmentationCode2
Multimodal Information Interaction for Medical Image SegmentationCode2
ASAM: Boosting Segment Anything Model with Adversarial TuningCode2
Aerial Lifting: Neural Urban Semantic and Building Instance Lifting from Aerial ImageryCode2
Multi-Scale Representations by Varying Window Attention for Semantic SegmentationCode2
Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentationCode2
Neighborhood Attention TransformerCode2
SlicerNNInteractive: A 3D Slicer extension for nnInteractiveCode2
nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space ModelCode2
DaViT: Dual Attention Vision TransformersCode2
BEFUnet: A Hybrid CNN-Transformer Architecture for Precise Medical Image SegmentationCode2
Coordinate Attention for Efficient Mobile Network DesignCode2
CorrCLIP: Reconstructing Correlations in CLIP with Off-the-Shelf Foundation Models for Open-Vocabulary Semantic SegmentationCode2
Occlusion-Aware Instance Segmentation via BiLayer Network ArchitecturesCode2
BEiT: BERT Pre-Training of Image TransformersCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310Unverified
2ViT-P (InternImage-H)Validation mIoU63.6Unverified
3ONE-PEACEValidation mIoU63Unverified
4M3I Pre-training (InternImage-H)Validation mIoU62.9Unverified
5InternImage-HValidation mIoU62.9Unverified
6BEiT-3Validation mIoU62.8Unverified
7EVAValidation mIoU62.3Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5Unverified
10FD-SwinV2-GValidation mIoU61.4Unverified