Incorporating Prior Knowledge to Enhance Self-Supervised Learning and Improve Generalization

Incorporating prior knowledge, such as shape information, into self-supervised learning (SSL) frameworks can reduce the reliance on extensive data augmentations, mitigate shortcut learning, and improve the robustness and generalization of the learned representations.