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SOTA
Généralisation de domaine
Domain Generalization On Terraincognita
Domain Generalization On Terraincognita
Métriques
Average Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
Average Accuracy
Paper Title
Repository
SIMPLE
57.6
SIMPLE: Specialized Model-Sample Matching for Domain Generalization
-
MoA (OpenCLIP, ViT-B/16)
52.8
Domain Generalization Using Large Pretrained Models with Mixture-of-Adapters
GMoE-S/16
48.5
Sparse Mixture-of-Experts are Domain Generalizable Learners
EOQ (ResNet-50)
53.2
QT-DoG: Quantization-aware Training for Domain Generalization
Fishr(ResNet-50)
47.4
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization
GMDG (ResNet-50)
51.1
Rethinking Multi-domain Generalization with A General Learning Objective
AdaClust (ResNet-50)
48.1
Adaptive Methods for Aggregated Domain Generalization
SIMPLE+
59.0
SIMPLE: Specialized Model-Sample Matching for Domain Generalization
-
MIRO (ResNet-50, SWAD)
52.9
Domain Generalization by Mutual-Information Regularization with Pre-trained Models
Model Ratatouille
52
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization
UniDG + CORAL + ConvNeXt-B
69.6
Towards Unified and Effective Domain Generalization
SWAD (ResNet-50)
50.0
SWAD: Domain Generalization by Seeking Flat Minima
SEDGE+
56.8
Domain Generalization using Pretrained Models without Fine-tuning
-
CADG
55.7
CADG: A Model Based on Cross Attention for Domain Generalization
-
Ensemble of Averages (ResNet-50)
52.3
Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization
SEDGE
56.8
Domain Generalization using Pretrained Models without Fine-tuning
-
GMDG (RegNetY-16GF, SWAD)
65
Rethinking Multi-domain Generalization with A General Learning Objective
GMDG (RegNetY-16GF)
60.7
Rethinking Multi-domain Generalization with A General Learning Objective
Ensemble of Averages (RegNetY-16GF)
61.1
Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization
VL2V-SD (CLIP, ViT-B/16)
58.54
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification
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