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 401450 of 1751 papers

TitleStatusHype
Towards Improving Adversarial Training of NLP ModelsCode1
AP-10K: A Benchmark for Animal Pose Estimation in the WildCode1
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training DebiasingCode1
Learning to Diversify for Single Domain GeneralizationCode1
Generalize then Adapt: Source-Free Domain Adaptive Semantic SegmentationCode1
Exploring Data Aggregation and Transformations to Generalize across Visual DomainsCode1
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency DomainCode1
Feature Stylization and Domain-aware Contrastive Learning for Domain GeneralizationCode1
Domain Generalization via Gradient SurgeryCode1
Anatomy of Domain Shift Impact on U-Net Layers in MRI SegmentationCode1
On the Challenges of Open World Recognitionunder Shifting Visual DomainsCode1
Which Invariance Should We Transfer? A Causal Minimax Learning ApproachCode1
Global Filter Networks for Image ClassificationCode1
Deep Learning for Face Anti-Spoofing: A SurveyCode1
VOLO: Vision Outlooker for Visual RecognitionCode1
X-FACT: A New Benchmark Dataset for Multilingual Fact CheckingCode1
Parameter-efficient Multi-task Fine-tuning for Transformers via Shared HypernetworksCode1
An Information-theoretic Approach to Distribution ShiftsCode1
Source-Free Open Compound Domain Adaptation in Semantic SegmentationCode1
Quantifying and Improving Transferability in Domain GeneralizationCode1
OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution GeneralizationCode1
Semi-Supervised Domain Generalization with Stochastic StyleMatchCode1
On Compositional Generalization of Neural Machine TranslationCode1
A Fourier-based Framework for Domain GeneralizationCode1
Medical Image Segmentation Using Squeeze-and-Expansion TransformersCode1
Weakly-Supervised Physically Unconstrained Gaze EstimationCode1
Towards Robust Vision TransformerCode1
A Bit More Bayesian: Domain-Invariant Learning with UncertaintyCode1
Simulating User Satisfaction for the Evaluation of Task-oriented Dialogue SystemsCode1
Learning to Perturb Word Embeddings for Out-of-distribution QACode1
Cross-Domain Few-Shot Classification via Adversarial Task AugmentationCode1
SelfReg: Self-supervised Contrastive Regularization for Domain GeneralizationCode1
Gradient Matching for Domain GeneralizationCode1
Deep Stable Learning for Out-Of-Distribution GeneralizationCode1
Learning to Synthesize Data for Semantic ParsingCode1
Contrastive Syn-to-Real GeneralizationCode1
S2R-DepthNet: Learning a Generalizable Depth-specific Structural RepresentationCode1
Progressive Domain Expansion Network for Single Domain GeneralizationCode1
RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective WhiteningCode1
Dynamic Domain Adaptation for Efficient InferenceCode1
Orthogonal Projection LossCode1
PureGaze: Purifying Gaze Feature for Generalizable Gaze EstimationCode1
NaturalProofs: Mathematical Theorem Proving in Natural LanguageCode1
An Empirical Framework for Domain Generalization in Clinical SettingsCode1
Treatment Effect Estimation using Invariant Risk MinimizationCode1
FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency SpaceCode1
Evaluation of Complexity Measures for Deep Learning Generalization in Medical Image AnalysisCode1
FSDR: Frequency Space Domain Randomization for Domain GeneralizationCode1
Group-wise Inhibition based Feature Regularization for Robust ClassificationCode1
Model-Based Domain GeneralizationCode1
Show:102550
← PrevPage 9 of 36Next →

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