SOTAVerified

Semantic Segmentation

Papers

Showing 13761400 of 14763 papers

TitleStatusHype
Augmentation-Free Dense Contrastive Knowledge Distillation for Efficient Semantic SegmentationCode1
Auto-Vocabulary Semantic SegmentationCode1
Semi-Supervised Active Learning for Semantic Segmentation in Unknown Environments Using Informative Path PlanningCode1
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image SegmentationCode1
Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised AdaptationCode1
Foundation Model Assisted Weakly Supervised Semantic SegmentationCode1
ShareCMP: Polarization-Aware RGB-P Semantic SegmentationCode1
Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation mapsCode1
AI-SAM: Automatic and Interactive Segment Anything ModelCode1
PartSLIP++: Enhancing Low-Shot 3D Part Segmentation via Multi-View Instance Segmentation and Maximum Likelihood EstimationCode1
SCLIP: Rethinking Self-Attention for Dense Vision-Language InferenceCode1
MobileUtr: Revisiting the relationship between light-weight CNN and Transformer for efficient medical image segmentationCode1
Generalization by Adaptation: Diffusion-Based Domain Extension for Domain-Generalized Semantic SegmentationCode1
Learning Efficient Unsupervised Satellite Image-based Building Damage DetectionCode1
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer LearningCode1
Geometrically-driven Aggregation for Zero-shot 3D Point Cloud UnderstandingCode1
Virtual Category Learning: A Semi-Supervised Learning Method for Dense Prediction with Extremely Limited LabelsCode1
Grounding Everything: Emerging Localization Properties in Vision-Language TransformersCode1
SPOT: Self-Training with Patch-Order Permutation for Object-Centric Learning with Autoregressive TransformersCode1
Efficient Multimodal Semantic Segmentation via Dual-Prompt LearningCode1
Generative Parameter-Efficient Fine-TuningCode1
Exploiting Diffusion Prior for Generalizable Dense PredictionCode1
Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image SegmentationCode1
Continual Learning for Image Segmentation with Dynamic QueryCode1
Focus on Query: Adversarial Mining Transformer for Few-Shot 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
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