SOTAVerified

Semantic Segmentation

Papers

Showing 38513875 of 14763 papers

TitleStatusHype
An Alternative to WSSS? An Empirical Study of the Segment Anything Model (SAM) on Weakly-Supervised Semantic Segmentation ProblemsCode1
Trapped in texture bias? A large scale comparison of deep instance segmentationCode1
Bidirectional Projection Network for Cross Dimension Scene UnderstandingCode1
MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained RepresentationsCode1
Diffusion Model is Secretly a Training-free Open Vocabulary Semantic SegmenterCode1
An End-to-end Framework For Low-Resolution Remote Sensing Semantic SegmentationCode1
Multi-Granularity Distillation Scheme Towards Lightweight Semi-Supervised Semantic SegmentationCode1
Diffusion for Out-of-Distribution Detection on Road Scenes and BeyondCode1
Bidirectional Self-Training with Multiple Anisotropic Prototypes for Domain Adaptive Semantic SegmentationCode1
DETRs with Hybrid MatchingCode1
Mining Contextual Information Beyond Image for Semantic SegmentationCode1
DEU-Net: Dual-Encoder U-Net for Automated Skin Lesion SegmentationCode1
Real-time Semantic Segmentation via Spatial-detail Guided Context PropagationCode1
Mining Relations among Cross-Frame Affinities for Video Semantic SegmentationCode1
Diffusion Model as Representation LearnerCode1
Triple-View Feature Learning for Medical Image SegmentationCode1
Devil is in Channels: Contrastive Single Domain Generalization for Medical Image SegmentationCode1
BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image SegmentationCode1
DeVIS: Making Deformable Transformers Work for Video Instance SegmentationCode1
Object Segmentation Without Labels with Large-Scale Generative ModelsCode1
Multi-Granularity Video Object SegmentationCode1
MISeval: a Metric Library for Medical Image Segmentation EvaluationCode1
Bilateral Network with Residual U-blocks and Dual-Guided Attention for Real-time Semantic SegmentationCode1
MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain GeneralizationCode1
An End-to-End Computer Vision Methodology for Quantitative MetallographyCode1
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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