3 accepted papers
Depth map captured by 3D cameras usually suffers from low resolution and insufficient quality, which limits its applications in real world. Thus, it is an essential task to develop efficient and effective techniques to handle various depth degradations. In this paper, we propose a color guided depth…
Single-view 3D reconstruction is a fundamental operation in computer vision. Although significant progress has been made by learning-based approaches, it remains a challenge that the reconstructed mesh is usually coarse since the geometric prior is ignored. In this paper, we propose a geometric prio…
The conventional sparse model relies on data representation in the form of vectors. It represents the vector-valued or vectorized one dimensional (1D) version of an signal as a highly sparse linear combination of basis atoms from a large dictionary. The 1D modeling, though simple, ignores the inhere…