SOTAVerified

Semantic Segmentation

Papers

Showing 95269550 of 14763 papers

TitleStatusHype
n-CPS: Generalising Cross Pseudo Supervision to n Networks for Semi-Supervised Semantic Segmentation0
Near-optimal Keypoint Sampling for Fast Pathological Lung Segmentation0
Near Real-time Hippocampus Segmentation Using Patch-based Canonical Neural Network0
Near, far: Patch-ordering enhances vision foundation models' scene understanding0
Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology0
Neighbor Does Matter: Density-Aware Contrastive Learning for Medical Semi-supervised Segmentation0
Neighborhood Spatial Aggregation MC Dropout for Efficient Uncertainty-aware Semantic Segmentation in Point Clouds0
Neither Quick Nor Proper -- Evaluation of QuickProp for Learning Deep Neural Networks0
NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation0
NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes0
ν-net: Deep Learning for Generalized Biventricular Cardiac Mass and Function Parameters0
Ω-Net (Omega-Net): Fully Automatic, Multi-View Cardiac MR Detection, Orientation, and Segmentation with Deep Neural Networks0
Network-Agnostic Knowledge Transfer for Medical Image Segmentation0
Network-Agnostic Knowledge Transfer from Latent Dataset for Medical Image Segmentation0
Network-Free, Unsupervised Semantic Segmentation With Synthetic Images0
Neural Architecture Search for Dense Prediction Tasks in Computer Vision0
Neural Architecture Search in operational context: a remote sensing case-study0
NeuralBF: Neural Bilateral Filtering for Top-down Instance Segmentation on Point Clouds0
Neural Data Server: A Large-Scale Search Engine for Transfer Learning Data0
NeuralDiff: Segmenting 3D objects that move in egocentric videos0
Neural Diffusion Distance for Image Segmentation0
Neural Field Conditioning Strategies for 2D Semantic Segmentation0
Neural Implicit Dense Semantic SLAM0
Neural LiDAR Fields for Novel View Synthesis0
NeurAll: Towards a Unified Visual Perception Model for Automated Driving0
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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