Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method

Understand

One of the challenges of computer vision is that it needs to adapt to color deviations in changeable environments.

• Therefore, minimizing the adverse effects of color deviation on the prediction is one of the main goals of vision task.
• Current solutions focus on using generative models to augment training data to enhance the invariance of input variation.
• However, such methods often introduce new noise, which limits the gain from generated data.