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 1501–1550 of 1751 papers

TitleStatusHype
Multi-View Domain Generalization for Visual Recognition—0
Multi-View Knowledge Distillation from Crowd Annotations for Out-of-Domain Generalization—0
Navigating Distribution Shifts in Medical Image Analysis: A Survey—0
NeRF-Gaze: A Head-Eye Redirection Parametric Model for Gaze Estimation—0
NeuGen: Amplifying the 'Neural' in Neural Radiance Fields for Domain Generalization—0
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers—0
NeuRN: Neuro-inspired Domain Generalization for Image Classification—0
Neuron Coverage-Guided Domain Generalization—0
NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning—0
Noise-Aware Generalization: Robustness to In-Domain Noise and Out-of-Domain Generalization—0
Non-Invasive Glucose Prediction System Enhanced by Mixed Linear Models and Meta-Forests for Domain Generalization—0
Hypernetwork-Driven Model Fusion for Federated Domain Generalization—0
Non-stationary Domain Generalization: Theory and Algorithm—0
Normalization Perturbation: A Simple Domain Generalization Method for Real-World Domain Shifts—0
NormAUG: Normalization-guided Augmentation for Domain Generalization—0
No Thing, Nothing: Highlighting Safety-Critical Classes for Robust LiDAR Semantic Segmentation in Adverse Weather—0
Not to Overfit or Underfit the Source Domains? An Empirical Study of Domain Generalization in Question Answering—0
Novel Human-Object Interaction Detection via Adversarial Domain Generalization—0
NuwaTS: a Foundation Model Mending Every Incomplete Time Series—0
Object Style Diffusion for Generalized Object Detection in Urban Scene—0
ODG-Q: Robust Quantization via Online Domain Generalization—0
OmniSSR: Zero-shot Omnidirectional Image Super-Resolution using Stable Diffusion Model—0
On Calibration and Out-of-domain Generalization—0
On Invariance Penalties for Risk Minimization—0
On Inverse Problems, Parameter Estimation, and Domain Generalization—0
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources—0
On the benefits of representation regularization in invariance based domain generalization—0
On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation—0
On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation—0
On the Consideration of AI Openness: Can Good Intent Be Abused?—0
On the Generalization of Handwritten Text Recognition Models—0
On the Generalization Properties of Deep Learning for Aircraft Fuel Flow Estimation Models—0
On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space—0
On the interplay between physical and content priors in deep learning for computational imaging—0
On the Mechanisms of Adversarial Data Augmentation for Robust and Adaptive Transfer Learning—0
OOD-Probe: A Neural Interpretation of Out-of-Domain Generalization—0
Open Domain Generalization with a Single Network by Regularization Exploiting Pre-trained Features—0
Open Domain Generalization with Domain-Augmented Meta-Learning—0
Operationalizing Specifications, In Addition to Test Sets for Evaluating Constrained Generative Models—0
Optimizing Specific and Shared Parameters for Efficient Parameter Tuning—0
Out-of-distribution Few-shot Learning For Edge Devices without Model Fine-tuning—0
Out-of-Domain Generalization from a Single Source: An Uncertainty Quantification Approach—0
Overcoming Data Inequality across Domains with Semi-Supervised Domain Generalization—0
ParisLuco3D: A high-quality target dataset for domain generalization of LiDAR perception—0
Partial Transportability for Domain Generalization—0
PDAML: A Pseudo Domain Adaptation Paradigm for Subject-independent EEG-based Emotion Recognition—0
PEER pressure: Model-to-Model Regularization for Single Source Domain Generalization—0
Person30K: A Dual-Meta Generalization Network for Person Re-Identification—0
Person Re-identification: A Retrospective on Domain Specific Open Challenges and Future Trends—0
Phase Matching for Out-of-Distribution Generalization—0
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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