SOTAVerified

Semantic Segmentation

Papers

Showing 53765400 of 14763 papers

TitleStatusHype
Revisiting the Encoding of Satellite Image Time SeriesCode1
Semi-Supervised Segmentation of Functional Tissue Units at the Cellular LevelCode1
Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous drivingCode1
CLUSTSEG: Clustering for Universal SegmentationCode1
Distributional Instance Segmentation: Modeling Uncertainty and High Confidence Predictions with Latent-MaskRCNN0
Extraction of volumetric indices from echocardiography: which deep learning solution for clinical use?Code1
LineFormer: Rethinking Line Chart Data Extraction as Instance SegmentationCode1
Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth LabelsCode1
DeepAqua: Self-Supervised Semantic Segmentation of Wetland Surface Water Extent with SAR Images using Knowledge DistillationCode1
An Alternative to WSSS? An Empirical Study of the Segment Anything Model (SAM) on Weakly-Supervised Semantic Segmentation ProblemsCode1
Exploring vision transformer layer choosing for semantic segmentation0
Neural LiDAR Fields for Novel View Synthesis0
RT-K-Net: Revisiting K-Net for Real-Time Panoptic SegmentationCode1
Segment Anything is A Good Pseudo-label Generator for Weakly Supervised Semantic Segmentation0
MASNet: A Robust Deep Marine Animal Segmentation NetworkCode0
MARS: Mask Attention Refinement with Sequential Quadtree Nodes for Car Damage Instance SegmentationCode1
CLIP-S^4: Language-Guided Self-Supervised Semantic Segmentation0
Bidirectional Copy-Paste for Semi-Supervised Medical Image SegmentationCode2
Point Cloud Semantic Segmentation0
PRSeg: A Lightweight Patch Rotate MLP Decoder for Semantic Segmentation0
Rethinking Boundary Detection in Deep Learning Models for Medical Image SegmentationCode1
TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene UnderstandingCode2
Detecting Novelties with Empty Classes0
Learning Structured Output Representations from Attributes using Deep Conditional Generative Models0
Brain Tumor Segmentation from MRI Images using Deep Learning Techniques0
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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