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 1376–1400 of 1751 papers

TitleStatusHype
Intrinsic Tensor Field Propagation in Large Language Models: A Novel Approach to Contextual Information Flow—0
Invariant Batch Normalization for Multi-source Domain Generalization—0
Invariant Causal Mechanisms through Distribution Matching—0
Invariant Content Synergistic Learning for Domain Generalization of Medical Image Segmentation—0
Invariant Correlation of Representation with Label—0
Invariant Information Bottleneck for Domain Generalization—0
Invariant Language Modeling—0
InvariantOODG: Learning Invariant Features of Point Clouds for Out-of-Distribution Generalization—0
End-to-End Lyrics Recognition with Self-supervised Learning—0
InvNorm: Domain Generalization for Object Detection in Gastrointestinal Endoscopy—0
Is Generative Modeling-based Stylization Necessary for Domain Adaptation in Regression Tasks?—0
Is Large-Scale Pretraining the Secret to Good Domain Generalization?—0
Is Multiple Object Tracking a Matter of Specialization?—0
FedWon: Triumphing Multi-domain Federated Learning Without Normalization—0
Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments—0
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation—0
Joint semi-supervised and contrastive learning enables domain generalization and multi-domain segmentation—0
Kernel Embedding Approaches to Orbit Determination of Spacecraft Clusters—0
Label-Efficient Domain Generalization via Collaborative Exploration and Generalization—0
LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization—0
Language-aware Domain Generalization Network for Cross-Scene Hyperspectral Image Classification—0
Large Language Models Meet Stance Detection: A Survey of Tasks, Methods, Applications, Challenges and Future Directions—0
LASSO: Latent Sub-spaces Orientation for Domain Generalization—0
Latent Feature Disentanglement For Visual Domain Generalization—0
LawngNLI: a multigranular, long-premise NLI benchmark for evaluating models’ in-domain generalization from short to long contexts—0
Show:102550
← PrevPage 56 of 71Next →
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