SOTAVerified

Semantic Segmentation

Papers

Showing 49014925 of 14763 papers

TitleStatusHype
Crop and Couple: cardiac image segmentation using interlinked specialist networksCode0
MorphMLP: An Efficient MLP-Like Backbone for Spatial-Temporal Representation LearningCode0
MSN: Efficient Online Mask Selection Network for Video Instance SegmentationCode0
Monocular Depth Estimation Using Cues Inspired by Biological Vision SystemsCode0
Modular Anti-noise Deep Learning Network for Robotic Grasp Detection Based on RGB ImagesCode0
Modular Sensor Fusion for Semantic SegmentationCode0
Monocular Depth Estimation with Hierarchical Fusion of Dilated CNNs and Soft-Weighted-Sum InferenceCode0
CRISP: A Framework for Cryo-EM Image Segmentation and Processing with Conditional Random FieldCode0
Addressing Model Vulnerability to Distributional Shifts over Image Transformation SetsCode0
Modernized Training of U-Net for Aerial Semantic SegmentationCode0
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired DataCode0
Model Guidance via Explanations Turns Image Classifiers into Segmentation ModelsCode0
Model-based inexact graph matching on top of CNNs for semantic scene understandingCode0
Temporal Unet: Sample Level Human Action Recognition using WiFiCode0
Model Doctor for Diagnosing and Treating Segmentation ErrorCode0
MoDA: Leveraging Motion Priors from Videos for Advancing Unsupervised Domain Adaptation in Semantic SegmentationCode0
ModaNet: A Large-Scale Street Fashion Dataset with Polygon AnnotationsCode0
CP2M: Clustered-Patch-Mixed Mosaic Augmentation for Aerial Image SegmentationCode0
AGSS-VOS: Attention Guided Single-Shot Video Object SegmentationCode0
COVERED, CollabOratiVE Robot Environment Dataset for 3D Semantic segmentationCode0
Coupling Global Context and Local Contents for Weakly-Supervised Semantic SegmentationCode0
More complex encoder is not all you needCode0
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization PathsCode0
MLSL: Multi-Level Self-Supervised Learning for Domain Adaptation with Spatially Independent and Semantically Consistent LabelingCode0
MLN-net: A multi-source medical image segmentation method for clustered microcalcifications using multiple layer normalizationCode0
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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