Domain Generalization
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Benchmarks
PACS
VizWiz-Classification
ImageNet-C
Office-Home
ImageNet-A
ImageNet-R
DomainNet
VLCS
TerraIncognita
ImageNet-Sketch
GTA5-to-Cityscapes
NICO Animal
NICO Vehicle
Stylized-ImageNet
Rotated Fashion-MNIST
CIFAR-100C
CIFAR-10C
Cityscapes to ACDC
LipitK
WildDash
Most implemented
Deep Residual Learning for Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
mixup: Beyond Empirical Risk Minimization
Aggregated Residual Transformations for Deep Neural Networks
Masked Autoencoders Are Scalable Vision Learners
Papers
GenCOPE: Syn2Real Generalized Category-Level Object Pose Estimation for Robotic Picking
Category-level object pose estimation (COPE), capable of generalizing to intra-class unknown objects, has become a core technique for robotic 3D scene understanding. However, existing COPE methods still require labor-int…
Domain GeneralizationScene UnderstandingPose EstimationAVSRBench: A Multi-Condition AVSR Benchmark
While AVSR has achieved sub-1% word error rates on the standard LRS3 benchmark, its reliance on broadcast speech obscures whether this reflects true generalization or just domain adaptation. To investigate this gap, we e…
Domain GeneralizationDomain AdaptationOpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining
World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Existing systems, however, are monolithic: the generative backbone, vi…
Domain GeneralizationPAPT++: Risk-Aware Adversarial Tuning and Generation for Single Domain Generalization
Single domain generalization (SDG) aims to learn a model from one labeled source domain that generalizes to unseen target domains. A common strategy is to enrich the source distribution with augmented or generated sample…
Domain GeneralizationLearning to Reason and Use Tools through Unsupervised Fine-Tuning in Task-Oriented Dialog Systems
Current dialogue systems struggle with dynamic information retrieval, often leading to hallucinations and lower response accuracy. We address this by adapting the ReAct framework for Task-Oriented Dialogue, enabling Larg…
Domain GeneralizationInformation RetrievalEXPOSE: Explainable and Domain-Robust Embeddings from Pathology Vision Foundation Models using Sparse Autoencoders
Vision Foundation Models (VFMs) are widely used in computational pathology but remain sensitive to domain shifts arising from variations in staining, tissue preparation, and scanner hardware. A key limitation is that VFM…
Domain Generalization