SOTAVerified

Semantic Segmentation

Papers

Showing 28512875 of 14763 papers

TitleStatusHype
Explainable Convolutional Neural Networks for Retinal Fundus Classification and Cutting-Edge Segmentation Models for Retinal Blood Vessels from Fundus ImagesCode1
Content-Consistent Matching for Domain Adaptive Semantic SegmentationCode1
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuningCode1
Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image SegmentationCode1
ISINet: An Instance-Based Approach for Surgical Instrument SegmentationCode1
Affinity Fusion Graph-based Framework for Natural Image SegmentationCode1
Context-aware Feature Generation for Zero-shot Semantic SegmentationCode1
Explicit Attention-Enhanced Fusion for RGB-Thermal Perception TasksCode1
Context-Aware Interaction Network for RGB-T Semantic SegmentationCode1
Context-Aware Mixup for Domain Adaptive Semantic SegmentationCode1
Exploiting Diffusion Prior for Generalizable Dense PredictionCode1
Context-Aware Pseudo-Label Refinement for Source-Free Domain Adaptive Fundus Image SegmentationCode1
ISNet: Integrate Image-Level and Semantic-Level Context for Semantic SegmentationCode1
Affinity Space Adaptation for Semantic Segmentation Across DomainsCode1
Multi-Stream Cellular Test-Time Adaptation of Real-Time Models Evolving in Dynamic EnvironmentsCode1
Exploiting Instance-based Mixed Sampling via Auxiliary Source Domain Supervision for Domain-adaptive Action DetectionCode1
ISTR: End-to-End Instance Segmentation with TransformersCode1
Context-Based Visual-Language Place RecognitionCode1
ISDNet: Integrating Shallow and Deep Networks for Efficient Ultra-High Resolution SegmentationCode1
Context Decoupling Augmentation for Weakly Supervised Semantic SegmentationCode1
AsymFormer: Asymmetrical Cross-Modal Representation Learning for Mobile Platform Real-Time RGB-D Semantic SegmentationCode1
CuVLER: Enhanced Unsupervised Object Discoveries through Exhaustive Self-Supervised TransformersCode1
iSeg: An Iterative Refinement-based Framework for Training-free SegmentationCode1
Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic SegmentationCode1
ISBNet: a 3D Point Cloud Instance Segmentation Network with Instance-aware Sampling and Box-aware Dynamic ConvolutionCode1
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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