SOTAVerified

Semantic Segmentation

Papers

Showing 40014025 of 14763 papers

TitleStatusHype
Discrepancy Matters: Learning from Inconsistent Decoder Features for Consistent Semi-supervised Medical Image SegmentationCode1
Using Diffusion Models to Generate Synthetic Labelled Data for Medical Image SegmentationCode1
Exploring Event-driven Dynamic Context for Accident Scene SegmentationCode1
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep StagingCode1
Evidence fusion with contextual discounting for multi-modality medical image segmentationCode1
Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated UncertaintyCode1
Boosting Semantic Human Matting with Coarse AnnotationsCode1
Evidential fully convolutional network for semantic segmentationCode1
V2M: Visual 2-Dimensional Mamba for Image Representation LearningCode1
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic SegmentationCode1
Variational Structured Attention Networks for Deep Visual Representation LearningCode1
VBLC: Visibility Boosting and Logit-Constraint Learning for Domain Adaptive Semantic Segmentation under Adverse ConditionsCode1
VDD: Varied Drone Dataset for Semantic SegmentationCode1
Discriminative Region Suppression for Weakly-Supervised Semantic SegmentationCode1
Boundary IoU: Improving Object-Centric Image Segmentation EvaluationCode1
Learning Spatio-Appearance Memory Network for High-Performance Visual TrackingCode1
Boundary Guided Context Aggregation for Semantic SegmentationCode1
VesselSAM: Leveraging SAM for Aortic Vessel Segmentation with AtrousLoRACode1
Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic SegmentationCode1
Video Class Agnostic Segmentation with Contrastive Learning for Autonomous DrivingCode1
Disentangled Non-Local Neural NetworksCode1
Disentangled Representations for Domain-generalized Cardiac SegmentationCode1
Disentangle then Parse:Night-time Semantic Segmentation with Illumination DisentanglementCode1
Disentangle then Parse: Night-time Semantic Segmentation with Illumination DisentanglementCode1
Explore the Potential of CLIP for Training-Free Open Vocabulary Semantic SegmentationCode1
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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