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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 676–700 of 1751 papers

TitleStatusHype
Benchmarking Azerbaijani Neural Machine Translation—0
A Flat Minima Perspective on Understanding Augmentations and Model Robustness—0
Generalizing Nucleus Recognition Model in Multi-source Images via Pruning—0
Generalizing to any diverse distribution: uniformity, gentle finetuning and rebalancing—0
Generative Classifier for Domain Generalization—0
Image-free Domain Generalization via CLIP for 3D Hand Pose Estimation—0
Depth-Sensitive Soft Suppression with RGB-D Inter-Modal Stylization Flow for Domain Generalization Semantic Segmentation—0
Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL—0
Denoising and Alignment: Rethinking Domain Generalization for Multimodal Face Anti-Spoofing—0
Bayesian Domain Invariant Learning via Posterior Generalization of Parameter Distributions—0
Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectives—0
BayeSeg: Bayesian Modeling for Medical Image Segmentation with Interpretable Generalizability—0
Adaptive Domain Generalization for Digital Pathology Images—0
Generalizing across Temporal Domains with Koopman Operators—0
Batch Normalization Embeddings for Deep Domain Generalization—0
Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport—0
Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)—0
Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition—0
Synthesizing Text-to-SQL Data from Weak and Strong LLMs—0
A Systematic Review of Generalization Research in Medical Image Classification—0
Deep Frequency Filtering for Domain Generalization—0
Generalization in Neural Networks: A Broad Survey—0
Deep Domain Generalization with Feature-norm Network—0
Deep Domain Generalization via Conditional Invariant Adversarial Networks—0
Two-Stage Adaptive Network for Semi-Supervised Cross-Domain Crater Detection under Varying Scenario Distributions—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