SOTAVerified

Semantic Segmentation

Papers

Showing 31013125 of 14763 papers

TitleStatusHype
NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter ScaleCode1
Visual Parser: Representing Part-whole Hierarchies with TransformersCode1
End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGBCode1
Locally Enhanced Self-Attention: Combining Self-Attention and Convolution as Local and Context TermsCode1
TransAttUnet: Multi-level Attention-guided U-Net with Transformer for Medical Image SegmentationCode1
Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic SegmentationCode1
Geographical Knowledge-driven Representation Learning for Remote Sensing ImagesCode1
A Spatial Guided Self-supervised Clustering Network for Medical Image SegmentationCode1
Anatomy of Domain Shift Impact on U-Net Layers in MRI SegmentationCode1
Capturing, Reconstructing, and Simulating: the UrbanScene3D DatasetCode1
Form2Seq : A Framework for Higher-Order Form Structure ExtractionCode1
Trans4Trans: Efficient Transformer for Transparent Object Segmentation to Help Visually Impaired People Navigate in the Real WorldCode1
Plot2Spectra: an Automatic Spectra Extraction ToolCode1
Contrastive Multimodal Fusion with TupleInfoNCECode1
On Model Calibration for Long-Tailed Object Detection and Instance SegmentationCode1
Similarity-Aware Fusion Network for 3D Semantic SegmentationCode1
Polarized Self-Attention: Towards High-quality Pixel-wise RegressionCode1
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image SegmentationCode1
UTNet: A Hybrid Transformer Architecture for Medical Image SegmentationCode1
A Survey on Deep Learning Technique for Video SegmentationCode1
CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped WindowsCode1
Focal Self-attention for Local-Global Interactions in Vision TransformersCode1
Inter Extreme Points Geodesics for End-to-End Weakly Supervised Image SegmentationCode1
DivergentNets: Medical Image Segmentation by Network EnsembleCode1
MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View UnderstandingCode1
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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
4InternImage-HValidation mIoU62.9Unverified
5M3I Pre-training (InternImage-H)Validation 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