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 551–575 of 1751 papers

TitleStatusHype
DomainVerse: A Benchmark Towards Real-World Distribution Shifts For Tuning-Free Adaptive Domain Generalization—0
Rethinking Multi-domain Generalization with A General Learning ObjectiveCode1
Suppress and Rebalance: Towards Generalized Multi-Modal Face Anti-SpoofingCode1
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery—0
Gradient Alignment for Cross-Domain Face Anti-SpoofingCode2
Learning Generalized Segmentation for Foggy-scenes by Bi-directional Wavelet GuidanceCode0
DANSK and DaCy 2.6.0: Domain Generalization of Danish Named Entity Recognition—0
Out-of-Domain Generalization in Dynamical Systems ReconstructionCode0
Prompt-Driven Dynamic Object-Centric Learning for Single Domain Generalization—0
ArcSin: Adaptive ranged cosine Similarity injected noise for Language-Driven Visual Tasks—0
StochCA: A Novel Approach for Exploiting Pretrained Models with Cross-AttentionCode0
GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm SegmentationCode0
Mitigating Biases of Large Language Models in Stance Detection with Counterfactual Augmented CalibrationCode0
Assessing generalization capability of text ranking models in Polish—0
Domain Generalization via Causal Adjustment for Cross-Domain Sentiment Analysis—0
A synthetic data approach for domain generalization of NLI models—0
Do causal predictors generalize better to new domains?Code1
Quantified Task Misalignment to Inform PEFT: An Exploration of Domain Generalization and Catastrophic Forgetting in CLIP—0
Reducing Texture Bias of Deep Neural Networks via Edge Enhancing DiffusionCode0
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction DataCode2
MetaTra: Meta-Learning for Generalized Trajectory Prediction in Unseen Domain—0
Generalizing across Temporal Domains with Koopman Operators—0
Hypernetwork-Driven Model Fusion for Federated Domain Generalization—0
Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning—0
Multisource Semisupervised Adversarial Domain Generalization Network for Cross-Scene Sea-Land Clutter Classification—0
Show:102550
← PrevPage 23 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