Examples are provided for pre-training a computer vision foundation model. A representative method comprises curating a pre-training database of image-text pairs from weakly labeled data. Language is encoded of text descriptions from the image-text pairs. The images of the image-text pairs are encoded using a hierarchical vision transformer with shifted windows and convolutional embedding. Based on the encoded images and the encoded language, the computer vision foundation model is pre-trained via unified image-text contrastive learning.