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 951–975 of 1751 papers

TitleStatusHype
A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites—0
A microservice-based framework for exploring data selection in cross-building knowledge transfer—0
A Multi-Mode Modulator for Multi-Domain Few-Shot Classification—0
Analyse s\'emantique robuste par apprentissage antagoniste pour la g\'en\'eralisation de domaine (Robust Semantic Parsing with Adversarial Learning for Domain Generalization )—0
Anatomical 3D Style Transfer Enabling Efficient Federated Learning with Extremely Low Communication Costs—0
An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers—0
Angular Visual Hardness—0
Ani-GIFs: A benchmark dataset for domain generalization of action recognition from GIFs—0
An Online Approach and Evaluation Method for Tracking People Across Cameras in Extremely Long Video Sequence—0
An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization—0
A Novel Cross-Perturbation for Single Domain Generalization—0
Any-Way Meta Learning—0
A Practical Synthesis of Detecting AI-Generated Textual, Visual, and Audio Content—0
A Rate-Distortion Approach to Domain Generalization—0
ArcSin: Adaptive ranged cosine Similarity injected noise for Language-Driven Visual Tasks—0
Are Domain Generalization Benchmarks with Accuracy on the Line Misspecified?—0
A Similarity Paradigm Through Textual Regularization Without Forgetting—0
A Simple Feature Augmentation for Domain Generalization—0
Assessing generalization capability of text ranking models in Polish—0
A Study of Domain Generalization on Ultrasound-based Multi-Class Segmentation of Arteries, Veins, Ligaments, and Nerves Using Transfer Learning—0
A Style and Semantic Memory Mechanism for Domain Generalization—0
A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools—0
A Survey of Large Language Model-Based Generative AI for Text-to-SQL: Benchmarks, Applications, Use Cases, and Challenges—0
A Survey on Out-of-Distribution Evaluation of Neural NLP Models—0
A synthetic data approach for domain generalization of NLI models—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