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

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Showing 801–850 of 1751 papers

TitleStatusHype
Shape Guided Gradient Voting for Domain Generalization—0
Multi-Granularity Hand Action DetectionCode1
FABLE : Fabric Anomaly Detection Automation ProcessCode0
Retrieving-to-Answer: Zero-Shot Video Question Answering with Frozen Large Language Models—0
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization—0
Modularity Trumps Invariance for Compositional RobustnessCode0
Distribution Shift Inversion for Out-of-Distribution PredictionCode1
Domain Information Control at Inference Time for Acoustic Scene ClassificationCode0
One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuningCode2
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacyCode0
FedWon: Triumphing Multi-domain Federated Learning Without Normalization—0
Devil is in Channels: Contrastive Single Domain Generalization for Medical Image SegmentationCode1
Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization—0
ContriMix: Scalable stain color augmentation for domain generalization without domain labels in digital pathology—0
Q: How to Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images!Code1
Toward More Accurate and Generalizable Evaluation Metrics for Task-Oriented Dialogs—0
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization—0
UNIDECOR: A Unified Deception Corpus for Cross-Corpus Deception DetectionCode0
Retrieval-Enhanced Visual Prompt Learning for Few-shot Classification—0
SASMU: boost the performance of generalized recognition model using synthetic face dataset—0
Federated Domain Generalization: A Survey—0
Is Generative Modeling-based Stylization Necessary for Domain Adaptation in Regression Tasks?—0
Consistency-guided Prompt Learning for Vision-Language ModelsCode1
Domain Generalization for Domain-Linked Classes—0
DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image SegmentationCode1
Signal Is Harder To Learn Than Bias: Debiasing with Focal LossCode0
Treasure in Distribution: A Domain Randomization based Multi-Source Domain Generalization for 2D Medical Image SegmentationCode1
Rethinking Masked Language Modeling for Chinese Spelling CorrectionCode1
Improving Generalization in Language Model-Based Text-to-SQL Semantic Parsing: Two Simple Semantic Boundary-Based TechniquesCode1
Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and EvaluationCode1
CNN Feature Map Augmentation for Single-Source Domain Generalization—0
Domain Aligned Prefix Averaging for Domain Generalization in Abstractive SummarizationCode0
Diversify Your Vision Datasets with Automatic Diffusion-Based AugmentationCode1
Meta Adaptive Task Sampling for Few-Domain Generalization—0
Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization—0
HARD: Hard Augmentations for Robust Distillation—0
Feature-aligned N-BEATS with Sinkhorn divergenceCode0
Learning Semantic Role Labeling from Compatible Label SequencesCode0
Rethinking the Evaluation Protocol of Domain GeneralizationCode1
Domain-Expanded ASTE: Rethinking Generalization in Aspect Sentiment Triplet ExtractionCode0
ReadMe++: Benchmarking Multilingual Language Models for Multi-Domain Readability AssessmentCode1
Adaptive Face Recognition Using Adversarial Information Network—0
Pulling Target to Source: A New Perspective on Domain Adaptive Semantic SegmentationCode0
Single Domain Dynamic Generalization for Iris Presentation Attack Detection—0
Rotation-Constrained Cross-View Feature Fusion for Multi-View Appearance-based Gaze EstimationCode0
POEM: Polarization of Embeddings for Domain-Invariant RepresentationsCode1
HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic SegmentationCode1
Domain Generalization Deep Graph Transformation—0
SUG: Single-dataset Unified Generalization for 3D Point Cloud ClassificationCode1
Learning to Generalize for Cross-domain QACode0
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All datasetsPACSVizWiz-ClassificationImageNet-COffice-HomeImageNet-AImageNet-RDomainNetVLCSTerraIncognitaGTA-to-Avg(Cityscapes,BDD,Mapillary)ImageNet-SketchGTA5 to Cityscapes

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SIMPLE+Average Accuracy99—Unverified
2PromptStyler (CLIP, ViT-L/14)Average Accuracy98.6—Unverified
3GMDG (RegNetY-16GF, SWAD)Average Accuracy97.9—Unverified
4D-Triplet(RegNetY-16GF)Average Accuracy97.6—Unverified
5MoA (OpenCLIP, ViT-B/16)Average Accuracy97.4—Unverified
6GMDG (e RegNetY-16GF)Average Accuracy97.3—Unverified
7PromptStyler (CLIP, ViT-B/16)Average Accuracy97.2—Unverified
8SPG (CLIP, ViT-B/16)Average Accuracy97—Unverified
9CAR-FT (CLIP, ViT-B/16)Average Accuracy96.8—Unverified
10MIRO (RegNetY-16GF, SWAD)Average Accuracy96.8—Unverified
#ModelMetricClaimedVerifiedStatus
1ViT-8/B-224Accuracy - Clean Images450—Unverified
2VOLO-D5Accuracy - All Images57.2—Unverified
3ConvNeXt-BAccuracy - All Images53.5—Unverified
4ResNeXt-101 32x16dAccuracy - All Images51.7—Unverified
5EfficientNet-B8 (advprop+autoaug)Accuracy - All Images50.5—Unverified
6EfficientNet-B7 (advprop+autoaug)Accuracy - All Images49.7—Unverified
7EfficientNet-B6 (advprop+autoaug)Accuracy - All Images49.6—Unverified
8EfficientNet-B5 (advprop+autoaug)Accuracy - All Images49.1—Unverified
9ViT-16/L-224Accuracy - All Images49—Unverified
10ResNet-50 (gn)Accuracy - All Images48.9—Unverified