HyperAI
Home
News
Latest Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
English
HyperAI
Toggle sidebar
Search the site…
⌘
K
Home
SOTA
Domain Generalization
Domain Generalization On Terraincognita
Domain Generalization On Terraincognita
Metrics
Average Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
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
0 of 30 row(s) selected.
Previous
Next