SOTAVerified

Domain Generalization

The idea of Domain Generalization is to learn from one or multiple training domains, to extract a domain-agnostic model which can be applied to an unseen domain

Source: Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning

Papers

Showing 451475 of 1751 papers

TitleStatusHype
Domain-General Crowd Counting in Unseen ScenariosCode1
Learning Robust Global Representations by Penalizing Local Predictive PowerCode1
ALOFT: A Lightweight MLP-like Architecture with Dynamic Low-frequency Transform for Domain GeneralizationCode1
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution GeneralizationCode1
Adaptive Risk Minimization: Learning to Adapt to Domain ShiftCode1
Improving Generalization in Language Model-Based Text-to-SQL Semantic Parsing: Two Simple Semantic Boundary-Based TechniquesCode1
Calibrated Feature Decomposition for Generalizable Person Re-IdentificationCode1
Improving the Transferability of Adversarial Examples with Arbitrary Style TransferCode1
Domain-Adversarial Training of Neural NetworksCode1
Improving robustness against common corruptions by covariate shift adaptationCode1
Improving Single Domain-Generalized Object Detection: A Focus on Diversification and AlignmentCode1
Sparse Mixture-of-Experts are Domain Generalizable LearnersCode1
Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive LearningCode1
Domain and Content Adaptive Convolution based Multi-Source Domain Generalization for Medical Image SegmentationCode1
Learning Fair Representation via Distributional Contrastive DisentanglementCode1
Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization AlgorithmsCode1
Domain Composition and Attention for Unseen-Domain Generalizable Medical Image SegmentationCode1
Domain Decorrelation with Potential Energy RankingCode1
DomainDrop: Suppressing Domain-Sensitive Channels for Domain GeneralizationCode1
Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic SegmentationCode1
In Search of Lost Domain GeneralizationCode1
InterNet: Unsupervised Cross-modal Homography Estimation Based on Interleaved Modality Transfer and Self-supervised Homography PredictionCode1
CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from SimulationCode1
Instance-Aware Domain Generalization for Face Anti-SpoofingCode1
Learning to Generalize: Meta-Learning for Domain GeneralizationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SIMPLE+Average Accuracy99Unverified
2PromptStyler (CLIP, ViT-L/14)Average Accuracy98.6Unverified
3GMDG (RegNetY-16GF, SWAD)Average Accuracy97.9Unverified
4D-Triplet(RegNetY-16GF)Average Accuracy97.6Unverified
5MoA (OpenCLIP, ViT-B/16)Average Accuracy97.4Unverified
6GMDG (e RegNetY-16GF)Average Accuracy97.3Unverified
7PromptStyler (CLIP, ViT-B/16)Average Accuracy97.2Unverified
8SPG (CLIP, ViT-B/16)Average Accuracy97Unverified
9CAR-FT (CLIP, ViT-B/16)Average Accuracy96.8Unverified
10MIRO (RegNetY-16GF, SWAD)Average Accuracy96.8Unverified
#ModelMetricClaimedVerifiedStatus
1ViT-8/B-224Accuracy - Clean Images450Unverified
2VOLO-D5Accuracy - All Images57.2Unverified
3ConvNeXt-BAccuracy - All Images53.5Unverified
4ResNeXt-101 32x16dAccuracy - All Images51.7Unverified
5EfficientNet-B8 (advprop+autoaug)Accuracy - All Images50.5Unverified
6EfficientNet-B7 (advprop+autoaug)Accuracy - All Images49.7Unverified
7EfficientNet-B6 (advprop+autoaug)Accuracy - All Images49.6Unverified
8EfficientNet-B5 (advprop+autoaug)Accuracy - All Images49.1Unverified
9ViT-16/L-224Accuracy - All Images49Unverified
10ResNet-50 (gn)Accuracy - All Images48.9Unverified