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 1151–1175 of 1751 papers

TitleStatusHype
Domain Generalization Emerges from Dreaming—0
Domain Generalization for 6D Pose Estimation Through NeRF-based Image Synthesis—0
Domain Generalization for Activity Recognition via Adaptive Feature Fusion—0
Domain Generalization for Cross-Receiver Radio Frequency Fingerprint Identification—0
Domain Generalization for Domain-Linked Classes—0
Domain Generalization for Endoscopic Image Segmentation by Disentangling Style-Content Information and SuperPixel Consistency—0
Domain Generalization for In-Orbit 6D Pose Estimation—0
Domain Generalization for Mammographic Image Analysis with Contrastive Learning—0
Domain Generalization for Medical Image Analysis: A Review—0
Domain generalization for retinal vessel segmentation via Hessian-based vector field—0
Domain Generalization for Robust Model-Based Offline Reinforcement Learning—0
Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters—0
Domain Generalization Guided by Large-Scale Pre-Trained Priors—0
Domain Generalization in Autonomous Driving: Evaluating YOLOv8s, RT-DETR, and YOLO-NAS with the ROAD-Almaty Dataset—0
Domain Generalization in Biosignal Classification—0
Domain Generalization in CLIP via Learning with Diverse Text Prompts—0
Domain Generalization in Computational Pathology: Survey and Guidelines—0
Domain generalization in deep learning-based mass detection in mammography: A large-scale multi-center study—0
Domain generalization in fetal brain MRI segmentation \ multi-reconstruction augmentation—0
Domain Generalization in Machine Learning Models for Wireless Communications: Concepts, State-of-the-Art, and Open Issues—0
Domain Generalization on Efficient Acoustic Scene Classification using Residual Normalization—0
Domain Generalization on Medical Imaging Classification using Episodic Training with Task Augmentation—0
Domain generalization Person Re-identification on Attention-aware multi-operation strategery—0
Domain Generalization through Audio-Visual Relative Norm Alignment in First Person Action Recognition—0
Domain Generalization through Meta-Learning: A Survey—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