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 15011550 of 1751 papers

TitleStatusHype
Towards contrast-agnostic soft segmentation of the spinal cordCode0
Domain Generalization by Solving Jigsaw PuzzlesCode0
Feature Distribution Matching for Federated Domain GeneralizationCode0
SFDA-rPPG: Source-Free Domain Adaptive Remote Physiological Measurement with Spatio-Temporal ConsistencyCode0
Multi-Source (Pre-)Training for Cross-Domain Measurement, Unit and Context ExtractionCode0
Domain Generalization by Rejecting Extreme AugmentationsCode0
Towards Data-Centric Face Anti-Spoofing: Improving Cross-domain Generalization via Physics-based Data SynthesisCode0
Multi-View Action Recognition Using Contrastive LearningCode0
Learning an Explicit Hyperparameter Prediction Function Conditioned on TasksCode0
Towards Data-Free Domain GeneralizationCode0
Domain Generalization by Marginal Transfer LearningCode0
LawngNLI: A Long-Premise Benchmark for In-Domain Generalization from Short to Long Contexts and for Implication-Based RetrievalCode0
LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and RestorationCode0
Language-Driven Dual Style Mixing for Single-Domain Generalized Object DetectionCode0
Joint covariate-alignment and concept-alignment: a framework for domain generalizationCode0
Signal Is Harder To Learn Than Bias: Debiasing with Focal LossCode0
IRS: Incremental Relationship-guided Segmentation for Digital PathologyCode0
Domain Generalization by Functional RegressionCode0
Boosting Cross-Domain Point Classification via Distilling Relational Priors from 2D TransformersCode0
SimpleDG: Simple Domain Generalization Baseline without Bells and WhistlesCode0
Invariant Models for Causal Transfer LearningCode0
Simple Disentanglement of Style and Content in Visual RepresentationsCode0
Simple Domain Generalization Methods are Strong Baselines for Open Domain GeneralizationCode0
Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual ClassificationCode0
Mixstyle-Entropy: Domain Generalization with Causal Intervention and PerturbationCode0
SIMPLE: Specialized Model-Sample Matching for Domain GeneralizationCode0
Unknown Domain Inconsistency Minimization for Domain GeneralizationCode0
Binary domain generalization for sparsifying binary neural networksCode0
Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain GeneralizationCode0
Domain-Generalizable Multiple-Domain ClusteringCode0
Domain-Expanded ASTE: Rethinking Generalization in Aspect Sentiment Triplet ExtractionCode0
Adversarial Semantic Hallucination for Domain Generalized Semantic SegmentationCode0
Single Domain Generalization for Alzheimer's Detection from 3D MRIs with Pseudo-Morphological Augmentations and Contrastive LearningCode0
Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image GeneratorsCode0
Domain-aware Triplet loss in Domain GeneralizationCode0
Single Domain Generalization for Few-Shot Counting via Universal Representation MatchingCode0
Information Subtraction: Learning Representations for Conditional EntropyCode0
Domain Aligned Prefix Averaging for Domain Generalization in Abstractive SummarizationCode0
Automated Domain Discovery from Multiple Sources to Improve Zero-Shot GeneralizationCode0
VideoDG: Generalizing Temporal Relations in Videos to Novel DomainsCode0
OCRT: Boosting Foundation Models in the Open World with Object-Concept-Relation TriadCode0
Adversarial Invariant LearningCode0
Improving Generalization with Domain Convex GameCode0
Adversarial Examples Improve Image RecognitionCode0
Adversarial Bayesian Augmentation for Single-Source Domain GeneralizationCode0
On Certifying and Improving Generalization to Unseen DomainsCode0
Improving Domain Generalization by Learning without Forgetting: Application in Retail CheckoutCode0
Improved RAMEN: Towards Domain Generalization for Visual Question AnsweringCode0
IMPaSh: A Novel Domain-shift Resistant Representation for Colorectal Cancer Tissue ClassificationCode0
IMO: Greedy Layer-Wise Sparse Representation Learning for Out-of-Distribution Text Classification with Pre-trained ModelsCode0
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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