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 1251–1300 of 1751 papers

TitleStatusHype
A Class-wise Non-salient Region Generalized Framework for Video Semantic Segmentation—0
Structural State Translation: Condition Transfer between Civil Structures Using Domain-Generalization for Structural Health Monitoring—0
Target Conditioned Representation Independence (TCRI); From Domain-Invariant to Domain-General Representations—0
Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image GeneratorsCode0
Domain Generalization with Correlated Style UncertaintyCode0
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization—0
Multi-View Knowledge Distillation from Crowd Annotations for Out-of-Domain Generalization—0
PoE: a Panel of Experts for Generalized Automatic Dialogue Assessment—0
Calibration-Free Driver Drowsiness Classification based on Manifold-Level AugmentationCode0
Synthetic-to-Real Domain Generalized Semantic Segmentation for 3D Indoor Point Clouds—0
LawngNLI: A Long-Premise Benchmark for In-Domain Generalization from Short to Long Contexts and for Implication-Based RetrievalCode0
Generalizable Person Re-Identification via Viewpoint Alignment and Fusion—0
Domain Adaptation and Generalization on Functional Medical Images: A Systematic Survey—0
Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation—0
Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning—0
Systematic Analysis for Pretrained Language Model Priming for Parameter-Efficient Fine-tuning—0
When Neural Networks Fail to Generalize? A Model Sensitivity PerspectiveCode0
Context-Aware Robust Fine-Tuning—0
Domain Generalization for Robust Model-Based Offline Reinforcement Learning—0
Direct-Effect Risk Minimization for Domain GeneralizationCode0
Domain generalization in fetal brain MRI segmentation \ multi-reconstruction augmentation—0
Cross-domain Transfer of defect features in technical domains based on partial target data—0
Operationalizing Specifications, In Addition to Test Sets for Evaluating Constrained Generative Models—0
Dynamic-Pix2Pix: Noise Injected cGAN for Modeling Input and Target Domain Joint Distributions with Limited Training DataCode0
HMOE: Hypernetwork-based Mixture of Experts for Domain Generalization—0
Towards Generalization on Real Domain for Single Image Dehazing via Meta-Learning—0
Generalization Beyond Feature Alignment: Concept Activation-Guided Contrastive Learning—0
DocuT5: Seq2seq SQL Generation with Table Documentation—0
Cross-Platform and Cross-Domain Abusive Language Detection with Supervised Contrastive Learning—0
Normalization Perturbation: A Simple Domain Generalization Method for Real-World Domain Shifts—0
Using Set Covering to Generate Databases for Holistic SteganalysisCode0
FIXED: Frustratingly Easy Domain Generalization with Mixup—0
Generalizable Re-Identification from Videos with Cycle Association—0
Contrastive Weighted Learning for Near-Infrared Gaze Estimation—0
Generalizability of Deep Adult Lung Segmentation Models to the Pediatric Population: A Retrospective Study—0
Learning to Learn Domain-invariant Parameters for Domain Generalization—0
Deep Multimodal Fusion for Generalizable Person Re-identificationCode0
Two-stage LLM Fine-tuning with Less Specialization and More Generalization—0
SAGE: Saliency-Guided Mixup with Optimal Rearrangements—0
Image-free Domain Generalization via CLIP for 3D Hand Pose Estimation—0
Domain Generalization through the Lens of Angular InvarianceCode0
Learning on the Job: Self-Rewarding Offline-to-Online Finetuning for Industrial Insertion of Novel Connectors from Vision—0
Trade-off between reconstruction loss and feature alignment for domain generalizationCode0
SimpleDG: Simple Domain Generalization Baseline without Bells and WhistlesCode0
OpenStance: Real-world Zero-shot Stance DetectionCode0
Toward domain generalized pruning by scoring out-of-distribution importance—0
Learning to Augment via Implicit Differentiation for Domain Generalization—0
Multi-Domain Long-Tailed Learning by Augmenting Disentangled RepresentationsCode0
Domain generalization Person Re-identification on Attention-aware multi-operation strategery—0
ODG-Q: Robust Quantization via Online Domain 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