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

Showing 16511700 of 1751 papers

TitleStatusHype
A Continual Development Methodology for Large-scale Multitask Dynamic ML SystemsCode0
Lesion Elevation Prediction from Skin Images Improves DiagnosisCode0
Prompting Diffusion Representations for Cross-Domain Semantic SegmentationCode0
FedStein: Enhancing Multi-Domain Federated Learning Through James-Stein EstimatorCode0
FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain GeneralizationCode0
Federated Domain Generalization via Prompt Learning and AggregationCode0
Prompt-OT: An Optimal Transport Regularization Paradigm for Knowledge Preservation in Vision-Language Model AdaptationCode0
Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated LearningCode0
A Causal Inspired Early-Branching Structure for Domain GeneralizationCode0
FedCCRL: Federated Domain Generalization with Cross-Client Representation LearningCode0
Feature Generation and Hypothesis Verification for Reliable Face Anti-SpoofingCode0
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case StudyCode0
Feature-Critic Networks for Heterogeneous Domain GeneralizationCode0
In-Context Learning of Linear Systems: Generalization Theory and Applications to Operator LearningCode0
Weighted Risk Invariance: Domain Generalization under Invariant Feature ShiftCode0
Pseudo Multi-Source Domain Generalization: Bridging the Gap Between Single and Multi-Source Domain GeneralizationCode0
Feature-aligned N-BEATS with Sinkhorn divergenceCode0
Pulling Target to Source: A New Perspective on Domain Adaptive Semantic SegmentationCode0
Algorithmic Fairness Generalization under Covariate and Dependence Shifts SimultaneouslyCode0
Fairness and Robustness in Invariant Learning: A Case Study in Toxicity ClassificationCode0
Deep Graph Laplacian Regularization for Robust Denoising of Real ImagesCode0
PushPull-Net: Inhibition-driven ResNet robust to image corruptionsCode0
Pyramid Adversarial Training Improves ViT PerformanceCode0
Fairness and Accuracy under Domain GeneralizationCode0
FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimalityCode0
Quality-Agnostic Image Recognition via Invertible DecoderCode0
Using Set Covering to Generate Databases for Holistic SteganalysisCode0
Failure Modes of Domain Generalization AlgorithmsCode0
CycleMix: Mixing Source Domains for Domain Generalization in Style-Dependent DataCode0
Towards Synchronous Memorizability and Generalizability with Site-Modulated Diffusion Replay for Cross-Site Continual SegmentationCode0
FABLE : Fabric Anomaly Detection Automation ProcessCode0
Exploring Language Model Generalization in Low-Resource Extractive QACode0
Exploring Flat Minima for Domain Generalization with Large Learning RatesCode0
Explaining Domain Shifts in Language: Concept erasing for Interpretable Image ClassificationCode0
A principled approach to model validation in domain generalizationCode0
Improving generalization by mimicking the human visual dietCode0
RARe: Retrieval Augmented Retrieval with In-Context ExamplesCode0
Trade-off between reconstruction loss and feature alignment for domain generalizationCode0
Episodic Training for Domain GeneralizationCode0
Current Limitations in Cyberbullying Detection: on Evaluation Criteria, Reproducibility, and Data ScarcityCode0
What's in a Latent? Leveraging Diffusion Latent Space for Domain GeneralizationCode0
Cross-Species Data Integration for Enhanced Layer Segmentation in Kidney PathologyCode0
TRAM: Bridging Trust Regions and Sharpness Aware MinimizationCode0
TACIT: A Target-Agnostic Feature Disentanglement Framework for Cross-Domain Text ClassificationCode0
Zero Shot Domain GeneralizationCode0
Recur, Attend or Convolve? On Whether Temporal Modeling Matters for Cross-Domain Robustness in Action RecognitionCode0
Cross-Domain Generalization of Neural Constituency ParsersCode0
Reducing Domain Gap by Reducing Style BiasCode0
Rethinking the Authorship Verification Experimental SetupsCode0
Reducing Texture Bias of Deep Neural Networks via Edge Enhancing DiffusionCode0
Show:102550
← PrevPage 34 of 36Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SIMPLE+Average Accuracy99Unverified
2PromptStyler (CLIP, ViT-L/14)Average Accuracy98.6Unverified
3GMDG (RegNetY-16GF, SWAD)Average Accuracy97.9Unverified
4D-Triplet(RegNetY-16GF)Average Accuracy97.6Unverified
5MoA (OpenCLIP, ViT-B/16)Average Accuracy97.4Unverified
6GMDG (e RegNetY-16GF)Average Accuracy97.3Unverified
7PromptStyler (CLIP, ViT-B/16)Average Accuracy97.2Unverified
8SPG (CLIP, ViT-B/16)Average Accuracy97Unverified
9CAR-FT (CLIP, ViT-B/16)Average Accuracy96.8Unverified
10MIRO (RegNetY-16GF, SWAD)Average Accuracy96.8Unverified
#ModelMetricClaimedVerifiedStatus
1ViT-8/B-224Accuracy - Clean Images450Unverified
2VOLO-D5Accuracy - All Images57.2Unverified
3ConvNeXt-BAccuracy - All Images53.5Unverified
4ResNeXt-101 32x16dAccuracy - All Images51.7Unverified
5EfficientNet-B8 (advprop+autoaug)Accuracy - All Images50.5Unverified
6EfficientNet-B7 (advprop+autoaug)Accuracy - All Images49.7Unverified
7EfficientNet-B6 (advprop+autoaug)Accuracy - All Images49.6Unverified
8EfficientNet-B5 (advprop+autoaug)Accuracy - All Images49.1Unverified
9ViT-16/L-224Accuracy - All Images49Unverified
10ResNet-50 (gn)Accuracy - All Images48.9Unverified