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 776800 of 1751 papers

TitleStatusHype
FedStein: Enhancing Multi-Domain Federated Learning Through James-Stein EstimatorCode0
Frequency-Based Federated Domain Generalization for Polyp SegmentationCode0
Identifying Knowledge Editing Types in Large Language ModelsCode0
From One to the Power of Many: Invariance to Multi-LiDAR Perception from Single-Sensor Datasets0
Exploring Language Model Generalization in Low-Resource Extractive QACode0
Exploring Acoustic Similarity in Emotional Speech and Music via Self-Supervised Representations0
Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain SchedulerCode0
Benchmarking Domain Generalization Algorithms in Computational PathologyCode0
AXCEL: Automated eXplainable Consistency Evaluation using LLMs0
FedGCA: Global Consistent Augmentation Based Single-Source Federated Domain Generalization0
Soft Segmented Randomization: Enhancing Domain Generalization in SAR-ATR for Synthetic-to-Measured0
Boosting Federated Domain Generalization: Understanding the Role of Advanced Pre-Trained Architectures0
Cross-Task Pretraining for Cross-Organ Cross-Scanner Adenocarcinoma Segmentation0
Learning to Generalize Unseen Domains via Multi-Source Meta Learning for Text Classification0
Domain Generalization for Endoscopic Image Segmentation by Disentangling Style-Content Information and SuperPixel Consistency0
Mixture of Prompt Learning for Vision Language Models0
SFDA-rPPG: Source-Free Domain Adaptive Remote Physiological Measurement with Spatio-Temporal ConsistencyCode0
In-Context Learning of Linear Systems: Generalization Theory and Applications to Operator LearningCode0
Template-based Multi-Domain Face Recognition0
Integrating Audio Narrations to Strengthen Domain Generalization in Multimodal First-Person Action Recognition0
Frequency Tracking Features for Data-Efficient Deep Siren IdentificationCode0
In-Situ Fine-Tuning of Wildlife Models in IoT-Enabled Camera Traps for Efficient Adaptation0
Non-Invasive Glucose Prediction System Enhanced by Mixed Linear Models and Meta-Forests for Domain Generalization0
Predicting Critical Heat Flux with Uncertainty Quantification and Domain Generalization Using Conditional Variational Autoencoders and Deep Neural Networks0
Medical Image Segmentation via Single-Source Domain Generalization with Random Amplitude Spectrum SynthesisCode0
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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