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Domain Generalization On Office Home

评估指标

Average Accuracy

评测结果

各个模型在此基准测试上的表现结果

Paper TitleRepository
MoA (OpenCLIP, ViT-B/16)90.6Domain Generalization Using Large Pretrained Models with Mixture-of-Adapters
PromptStyler (CLIP, ViT-L/14)89.1PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization
UniDG + CORAL + ConvNeXt-B88.9Towards Unified and Effective Domain Generalization
SIMPLE+87.7SIMPLE: Specialized Model-Sample Matching for Domain Generalization-
VL2V-SD (CLIP, ViT-B/16)87.38Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification
CAR-FT (CLIP, ViT-B/16)85.7Context-Aware Robust Fine-Tuning-
GMDG (RegNetY-16GF, SWAD)84.7Rethinking Multi-domain Generalization with A General Learning Objective
SIMPLE84.6SIMPLE: Specialized Model-Sample Matching for Domain Generalization-
Ensemble of Averages (RegNetY-16GF)83.9Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization
PromptStyler (CLIP, ViT-B/16)83.6PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization
SPG (CLIP, ViT-B/16)83.6Soft Prompt Generation for Domain Generalization
MIRO (RegNetY-16GF, SWAD)83.3Domain Generalization by Mutual-Information Regularization with Pre-trained Models
D-Triplet(RegNetY-16GF)82.6Domain-aware Triplet loss in Domain Generalization
GMDG (RegNetY-16GF)80.8Rethinking Multi-domain Generalization with A General Learning Objective
SEDGE+80.7Domain Generalization using Pretrained Models without Fine-tuning-
Ensemble of Averages (ResNeXt-50 32x4d)80.2Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization
CADG79.9CADG: A Model Based on Cross Attention for Domain Generalization-
SEDGE79.9Domain Generalization using Pretrained Models without Fine-tuning-
GMoE-S/1674.2Sparse Mixture-of-Experts are Domain Generalizable Learners
SPG (CLIP, ResNet-50)73.8Soft Prompt Generation for Domain Generalization
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Domain Generalization On Office Home | SOTA | HyperAI超神经