Abstract
Depth can be estimated with high accuracy by using deep learning. However, for camera pairs with long baseline, the accuracy of disparity is reduced because of the visual difference between left and right images. In this paper, we propose disparity estimation method based on feature map correlation using contrastive learning. By taking into account visual difference between the left and right images, we improve the accuracy of disparity estimation. Experimental results show that the proposed method improves accuracy within 20 m.
