SOTAVerified

Semantic Segmentation

Papers

Showing 38013825 of 14763 papers

TitleStatusHype
Exploiting Instance-based Mixed Sampling via Auxiliary Source Domain Supervision for Domain-adaptive Action DetectionCode1
Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small DatasetsCode1
Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve BackbonesCode1
DeRIS: Decoupling Perception and Cognition for Enhanced Referring Image Segmentation through Loopback SynergyCode1
Anabranch Network for Camouflaged Object SegmentationCode1
DermSynth3D: Synthesis of in-the-wild Annotated Dermatology ImagesCode1
DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image SegmentationCode1
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-RefinementCode1
3D-to-2D Distillation for Indoor Scene ParsingCode1
Exploiting Temporal State Space Sharing for Video Semantic SegmentationCode1
An Accelerated Pipeline for Multi-label Renal Pathology Image Segmentation at the Whole Slide Image LevelCode1
The Fully Convolutional Transformer for Medical Image SegmentationCode1
Beyond the Prototype: Divide-and-conquer Proxies for Few-shot SegmentationCode1
Exploring Cross-Image Pixel Contrast for Semantic SegmentationCode1
BoxSnake: Polygonal Instance Segmentation with Box SupervisionCode1
4D Unsupervised Object DiscoveryCode1
Explain Any Concept: Segment Anything Meets Concept-Based ExplanationCode1
The Marine Debris Dataset for Forward-Looking Sonar Semantic SegmentationCode1
BFANet: Revisiting 3D Semantic Segmentation with Boundary Feature AnalysisCode1
The Need for Speed: Pruning Transformers with One RecipeCode1
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuningCode1
Leveraging SO(3)-steerable convolutions for pose-robust semantic segmentation in 3D medical dataCode1
BHSD: A 3D Multi-Class Brain Hemorrhage Segmentation DatasetCode1
Detect Any Shadow: Segment Anything for Video Shadow DetectionCode1
Explainable Convolutional Neural Networks for Retinal Fundus Classification and Cutting-Edge Segmentation Models for Retinal Blood Vessels from Fundus ImagesCode1
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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