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 1351–1400 of 1751 papers

TitleStatusHype
Joint covariate-alignment and concept-alignment: a framework for domain generalizationCode0
Benchmarking Azerbaijani Neural Machine Translation—0
Diversity Boosted Learning for Domain Generalization with Large Number of Domains—0
Self-Distilled Vision Transformer for Domain GeneralizationCode0
Domain-invariant Feature Exploration for Domain Generalization—0
Domain Generalization for Activity Recognition via Adaptive Feature Fusion—0
Measuring and signing fairness as performance under multiple stakeholder distributions—0
Adaptive Mixture of Experts Learning for Generalizable Face Anti-Spoofing—0
Doge Tickets: Uncovering Domain-general Language Models by Playing Lottery TicketsCode0
Improving Domain Generalization by Learning without Forgetting: Application in Retail CheckoutCode0
Adversarial Style Augmentation for Domain Generalized Urban-Scene SegmentationCode0
Generalizing to Unseen Domains with Wasserstein Distributional Robustness under Limited Source Knowledge—0
Style Interleaved Learning for Generalizable Person Re-identificationCode0
Predicting Out-of-Domain Generalization with Neighborhood Invariance—0
Temporal Generalization for Spoken Language Understanding—0
Single-domain Generalization in Medical Image Segmentation via Test-time Adaptation from Shape Dictionary—0
Domain Agnostic Few-shot Learning for Speaker Verification—0
Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation—0
Gated Domain Units for Multi-source Domain GeneralizationCode0
Domain Generalization with Relaxed Instance Frequency-wise Normalization for Multi-device Acoustic Scene Classification—0
On Certifying and Improving Generalization to Unseen DomainsCode0
Invariant Causal Mechanisms through Distribution Matching—0
Test-time image-to-image translation ensembling improves out-of-distribution generalization in histopathology—0
Finding Diverse and Predictable Subgraphs for Graph Domain Generalization—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
Towards Generalizable Person Re-identification with a Bi-stream Generative Model—0
Self-Supervised Learning for Videos: A SurveyCode0
The Importance of Background Information for Out of Distribution Generalization—0
Domain Generalization via Selective Consistency Regularization for Time Series Classification—0
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization—0
Improving generalization by mimicking the human visual dietCode0
Slimmable Domain AdaptationCode0
INDIGO: Intrinsic Multimodality for Domain Generalization—0
Improving Pre-trained Language Model Fine-tuning with Noise Stability Regularization—0
Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods—0
Contrastive Centroid Supervision Alleviates Domain Shift in Medical Image Classification—0
Evolving Domain Generalization—0
Supporting Vision-Language Model Inference with Causality-pruning Knowledge Prompt—0
Test-time Batch Normalization—0
Generalizing to Evolving Domains with Latent Structure-Aware Sequential AutoencoderCode0
Not to Overfit or Underfit the Source Domains? An Empirical Study of Domain Generalization in Question Answering—0
Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation—0
InvNorm: Domain Generalization for Object Detection in Gastrointestinal Endoscopy—0
Invariant Content Synergistic Learning for Domain Generalization of Medical Image Segmentation—0
EllSeg-Gen, towards Domain Generalization for head-mounted eyetrackingCode0
Bridging the Generalization Gap in Text-to-SQL Parsing with Schema Expansion—0
Benchmarking Domain Generalization on EEG-based Emotion Recognition—0
MetaSets: Meta-Learning on Point Sets for Generalizable Representations—0
Prototype-based Domain Generalization Framework for Subject-Independent Brain-Computer Interfaces—0
Activation Regression for Continuous Domain Generalization with Applications to Crop ClassificationCode0
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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