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Domain Adaptation

1154 directly classified papers

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Papers

Gradual Source Domain Expansion for Unsupervised Domain Adaptation WACV 2024
Robust Learning via Conditional Prevalence Adjustment WACV 2024
FG-Net: Facial Action Unit Detection With Generalizable Pyramidal Features WACV 2024
From Denoising Training To Test-Time Adaptation: Enhancing Domain Generalization for Medical Image Segmentation WACV 2024
Gradual Domain Adaptation: Theory and Algorithms JMLR 2024
CoD: Coherent Detection of Entities From Images With Multiple Modalities WACV 2024
Nearest Neighbor Sampling for Covariate Shift Adaptation JMLR 2024
Feed-Forward Latent Domain Adaptation WACV 2024
D3GU: Multi-Target Active Domain Adaptation via Enhancing Domain Alignment WACV 2024
Functional optimal transport: regularized map estimation and domain adaptation for functional data JMLR 2024
Stochastic Binary Network for Universal Domain Adaptation WACV 2024
Rank and Align: Towards Effective Source-free Graph Domain Adaptation IJCAI 2024
Disentangling Domain and General Representations for Time Series Classification IJCAI 2024
More is Better: Deep Domain Adaptation with Multiple Sources IJCAI 2024
Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization JMLR 2024
Towards Dynamic-Prompting Collaboration for Source-Free Domain Adaptation IJCAI 2024
Cross-Scale Domain Adaptation with Comprehensive Information for Pansharpening IJCAI 2024
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria JMLR 2024
Rethinking Correlation Learning via Label Prior for Open Set Domain Adaptation IJCAI 2024
Universal Semi-Supervised Model Adaptation via Collaborative Consistency Training WACV 2024
Designing a Hybrid Neural System To Learn Real-World Crack Segmentation From Fractal-Based Simulation WACV 2024
Fast One-Stage Unsupervised Domain Adaptive Person Search IJCAI 2024
Optimal Graph Learning and Nuclear Norm Maximization for Deep Cross-Domain Robust Label Propagation IJCAI 2024
MoP-CLIP: A Mixture of Prompt-Tuned CLIP Models for Domain Incremental Learning WACV 2024
Aligning Non-Causal Factors for Transformer-Based Source-Free Domain Adaptation WACV 2024