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 1451–1475 of 1751 papers

TitleStatusHype
Rethinking the Authorship Verification Experimental SetupsCode0
3D-VField: Adversarial Augmentation of Point Clouds for Domain Generalization in 3D Object Detection—0
PLACE dropout: A Progressive Layer-wise and Channel-wise Dropout for Domain GeneralizationCode0
Unsupervised Domain Adaptation for Semantic Image Segmentation: a Comprehensive Survey—0
Causal-based Time Series Domain Generalization for Vehicle Intention Prediction—0
An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers—0
Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization—0
Adversarial Teacher-Student Representation Learning for Domain GeneralizationCode0
Pyramid Adversarial Training Improves ViT PerformanceCode0
Unsupervised Domain Generalization for Person Re-identification: A Domain-specific Adaptive FrameworkCode0
TAL: Two-stream Adaptive Learning for Generalizable Person Re-identification—0
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources—0
Failure Modes of Domain Generalization AlgorithmsCode0
Confounder Identification-free Causal Visual Feature Learning—0
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster AssignmentCode0
Discrete Representations Strengthen Vision Transformer RobustnessCode0
Federated Learning with Domain Generalization—0
Invariant Language Modeling—0
Domain Generalization on Efficient Acoustic Scene Classification using Residual Normalization—0
How to Select One Among All ? An Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding—0
DEX: Domain Embedding Expansion for Generalized Person Re-identification—0
UniFed: A Unified Framework for Federated Learning on Non-IID Image Features—0
Domain Generalization through Audio-Visual Relative Norm Alignment in First Person Action Recognition—0
On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation—0
Reappraising Domain Generalization in Neural Networks—0
Show:102550
← PrevPage 59 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