Pan, Liyuan; Dai, Yuchao; Liu, Miaomiao; Porikli, Fatih
We aim at predicting a complete and high-resolution depth map from incomplete, sparse and noisy depth measurements. Existing methods handle this problem either by exploiting various regularizations on the depth maps directly or resorting to learning based methods. When the corresponding color images are available, the correlation between the depth maps and the color images are used to improve the completion performance, assuming the color images are clean and sharp. However, in real world...[Show more]
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.