We aim to use RGB-D images to help recognizing RGB images.
The correlation between RGB and depth images in source domain is maximized.
The cross domain and cross modal constraints are jointly incorporated in the model.
A unified framework is presented to learn the classifier parameters.
Extensive experiment results show that depth information is useful for DA problems.