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 201250 of 1751 papers

TitleStatusHype
Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity RecognitionCode1
Aggregated Residual Transformations for Deep Neural NetworksCode1
Crafting Distribution Shifts for Validation and Training in Single Source Domain GeneralizationCode1
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent AlignmentCode1
Beyond Model Adaptation at Test Time: A SurveyCode1
Beyond Normal: On the Evaluation of Mutual Information EstimatorsCode1
Dynamic Domain Adaptation for Efficient InferenceCode1
Disentangling Masked Autoencoders for Unsupervised Domain GeneralizationCode1
Leveraging Vision-Language Models for Improving Domain Generalization in Image ClassificationCode1
BioBridge: Bridging Biomedical Foundation Models via Knowledge GraphsCode1
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case GeneralizationCode1
Distilling Out-of-Distribution Robustness from Vision-Language Foundation ModelsCode1
Fishr: Invariant Gradient Variances for Out-of-Distribution GeneralizationCode1
Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and TransferabilityCode1
Dynamic Domain GeneralizationCode1
Domain-Adversarial Training of Neural NetworksCode1
Borrowing Knowledge From Pre-trained Language Model: A New Data-efficient Visual Learning ParadigmCode1
Diversify Your Vision Datasets with Automatic Diffusion-Based AugmentationCode1
Cross Contrasting Feature Perturbation for Domain GeneralizationCode1
Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain DatasetsCode1
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution GeneralizationCode1
GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable PartsCode1
AAPL: Adding Attributes to Prompt Learning for Vision-Language ModelsCode1
Bridging the Source-to-target Gap for Cross-domain Person Re-Identification with Intermediate DomainsCode1
Cross-Domain Few-Shot Classification via Learned Feature-Wise TransformationCode1
ALOFT: A Lightweight MLP-like Architecture with Dynamic Low-frequency Transform for Domain GeneralizationCode1
Adaptive Risk Minimization: Learning to Adapt to Domain ShiftCode1
Calibrated Feature Decomposition for Generalizable Person Re-IdentificationCode1
Domain Decorrelation with Potential Energy RankingCode1
DomainDrop: Suppressing Domain-Sensitive Channels for Domain GeneralizationCode1
Efficient and Effective Augmentation Strategy for Adversarial TrainingCode1
AMAES: Augmented Masked Autoencoder Pretraining on Public Brain MRI Data for 3D-Native SegmentationCode1
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency DomainCode1
Domain-General Crowd Counting in Unseen ScenariosCode1
DPStyler: Dynamic PromptStyler for Source-Free Domain GeneralizationCode1
CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from SimulationCode1
ASPS: Augmented Segment Anything Model for Polyp SegmentationCode1
Causal Balancing for Domain GeneralizationCode1
A Closer Look at Few-shot ClassificationCode1
Domain Generalization for Object Recognition with Multi-task AutoencodersCode1
Anatomy of Domain Shift Impact on U-Net Layers in MRI SegmentationCode1
Gradient Matching for Domain GeneralizationCode1
Causality Inspired Representation Learning for Domain GeneralizationCode1
Causality-inspired Single-source Domain Generalization for Medical Image SegmentationCode1
Which Invariance Should We Transfer? A Causal Minimax Learning ApproachCode1
Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive LearningCode1
CDDSA: Contrastive Domain Disentanglement and Style Augmentation for Generalizable Medical Image SegmentationCode1
UniDA3D: Unified Domain Adaptive 3D Semantic Segmentation PipelineCode1
Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person MatchingCode1
Contrastive Syn-to-Real 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