Point cloud completion is a generation and estimation issue derived from the partial point
clouds, which plays a vital role in the applications of 3D computer vision. The progress of …

Point cloud completion has become increasingly popular among generation tasks of 3D
point clouds, as it is a challenging yet indispensable problem to recover the complete shape …

Point cloud completion aims to recover the completed 3D shape of an object from its partial
observation. A common strategy is to encode the observed points to a global feature vector …

In this paper, we propose a novel network, SVDFormer, to tackle two specific challenges in
point cloud completion: understanding faithful global shapes from incomplete point clouds …

Point cloud completion is able to estimate the complete point cloud starting from the missing
point cloud, which obtains higher quality point cloud data for widely used in remote sensing …

While previous studies have demonstrated successful 3D object shape completion with a
sufficient number of points they often fail in scenarios when a few points eg tens of points are …

Most existing point cloud completion methods suffer from the discrete nature of point clouds
and the unstructured prediction of points in local regions, which makes it difficult to reveal …

Guided depth completion aims to recover dense depth maps by propagating depth
information from the given pixels to the remaining ones under the guidance of RGB images …

Point cloud completion referring to completing 3D shapes from partial 3D point clouds is a
fundamental problem for 3D point cloud analysis tasks. Benefiting from the development of …

In this paper we explore the recent topic of point cloud completion, guided by an auxiliary
image. We show how it is possible to effectively combine the information from the two …