2 papers
cs.CV2025
Disentangled Geometric Alignment with Adaptive Contrastive Perturbation for Reliable Domain Transfer
Emma Collins, Myungseo wong, Kim Yun +2
Despite progress in geometry-aware domain adaptation, current methods such as GAMA still suffer from two unresolved issues: (1) insufficient disentanglement of task-relevant and ta…
cs.CV2025
Geometrically Regularized Transfer Learning with On-Manifold and Off-Manifold Perturbation
Hana Satou, Alan Mitkiy, Emma Collins +1
Transfer learning under domain shift remains a fundamental challenge due to the divergence between source and target data manifolds. In this paper, we propose MAADA (Manifold-Aware…