SOTAVerified

Single-Source Domain Generalization

In this task a model is trained in a single source domain and then it is tested in a number of target domains

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–48 of 48 papers

TitleStatusHype
Test-Time Domain Generalization via Universe Learning: A Multi-Graph Matching Approach for Medical Image SegmentationCode2
Avoiding Shortcuts: Enhancing Channel-Robust Specific Emitter Identification via Single-Source Domain GeneralizationCode2
Crafting Distribution Shifts for Validation and Training in Single Source Domain GeneralizationCode1
Prompting Segment Anything Model with Domain-Adaptive Prototype for Generalizable Medical Image SegmentationCode1
Structure-Aware Single-Source Generalization with Pixel-Level Disentanglement for Joint Optic Disc and Cup SegmentationCode1
RaffeSDG: Random Frequency Filtering enabled Single-source Domain Generalization for Medical Image SegmentationCode1
Language Guided Domain Generalized Medical Image SegmentationCode1
Leveraging SAM for Single-Source Domain Generalization in Medical Image SegmentationCode1
Frequency-mixed Single-source Domain Generalization for Medical Image SegmentationCode1
Improved Test-Time Adaptation for Domain GeneralizationCode1
Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image SegmentationCode1
Cross-Domain Ensemble Distillation for Domain GeneralizationCode1
Improving Diversity with Adversarially Learned Transformations for Domain GeneralizationCode1
Attention Consistency on Visual Corruptions for Single-Source Domain GeneralizationCode1
Causality-inspired Single-source Domain Generalization for Medical Image SegmentationCode1
Learning to Diversify for Single Domain GeneralizationCode1
SelfReg: Self-supervised Contrastive Regularization for Domain GeneralizationCode1
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations—0
Pseudo Multi-Source Domain Generalization: Bridging the Gap Between Single and Multi-Source Domain GeneralizationCode0
PEER pressure: Model-to-Model Regularization for Single Source Domain Generalization—0
Mono2D: A Trainable Monogenic Layer for Robust Knee Cartilage Segmentation on Out-of-Distribution 2D Ultrasound Data—0
Color-Quality Invariance for Robust Medical Image SegmentationCode0
Rethinking domain generalization in medical image segmentation: One image as one domain—0
Multisource Collaborative Domain Generalization for Cross-Scene Remote Sensing Image Classification—0
TIDE: Training Locally Interpretable Domain Generalization Models Enables Test-time Correction—0
DRIFTS: Optimizing Domain Randomization with Synthetic Data and Weight Interpolation for Fetal Brain Tissue Segmentation—0
Generalizable Single-Source Cross-modality Medical Image Segmentation via Invariant Causal MechanismsCode0
Domain Expansion and Boundary Growth for Open-Set Single-Source Domain Generalization—0
Aligned Divergent Pathways for Omni-Domain Generalized Person Re-Identification—0
Medical Image Segmentation via Single-Source Domain Generalization with Random Amplitude Spectrum SynthesisCode0
Double Gradient Reversal Network for Single-Source Domain Generalization in Multi-mode Fault Diagnosis—0
FIESTA: Fourier-Based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation—0
WIDIn: Wording Image for Domain-Invariant Representation in Single-Source Domain Generalization—0
Unbiased Faster R-CNN for Single-source Domain Generalized Object Detection—0
MoreStyle: Relax Low-frequency Constraint of Fourier-based Image Reconstruction in Generalizable Medical Image SegmentationCode0
HD Maps are Lane Detection Generalizers: A Novel Generative Framework for Single-Source Domain Generalization—0
Adversarial Bayesian Augmentation for Single-Source Domain GeneralizationCode0
CNN Feature Map Augmentation for Single-Source Domain Generalization—0
Frequency Decomposition to Tap the Potential of Single Domain for Generalization—0
Meta-causal Learning for Single Domain Generalization—0
Progressive Random Convolutions for Single Domain Generalization—0
Center-aware Adversarial Augmentation for Single Domain Generalization—0
DGSS : Domain Generalized Semantic Segmentation using Iterative Style Mining and Latent Representation Alignment—0
Meta Distribution Alignment for Generalizable Person Re-IdentificationCode0
Meta Convolutional Neural Networks for Single Domain Generalization—0
Geometric and Textural Augmentation for Domain Gap ReductionCode0
Encouraging Intra-Class Diversity Through a Reverse Contrastive Loss for Better Single-Source Domain Generalization—0
Reducing Domain Gap by Reducing Style BiasCode0
Show:102550
All datasetsPACSDigits-five

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Crafting-Shifts(ResNet18)Accuracy70.37—Unverified
2MCL (ResNet18)Accuracy69.86—Unverified
3ProRandConv (ResNet18)Accuracy68.88—Unverified
4CADA (ResNet18)Accuracy68.41—Unverified
5ITTA (ResNet18)Accuracy68.4—Unverified
6XDED (ResNet18)Accuracy66.5—Unverified
7ABA (ResNet18)Accuracy66.36—Unverified
8GeoTexAug (ResNet18)Accuracy65—Unverified
9SagNet (ResNet18)Accuracy61.9—Unverified
10SelfReg (ResNet18)Accuracy59.59—Unverified
#ModelMetricClaimedVerifiedStatus
1Crafting-Shifts(LeNet)Accuracy82.61—Unverified
2ProRandConv (LeNet)Accuracy81.35—Unverified
3CADA (LeNet)Accuracy80.56—Unverified
4MCL (LeNet)Accuracy78.82—Unverified
5MetaCNN (LeNet)Accuracy78.76—Unverified
6ABA (LeNet)Accuracy76.72—Unverified
7L2D (LeNet)Accuracy74.46—Unverified