Deep learning has exploded in the public consciousness, primarily as predictive and
analytical products suffuse our world, in the form of numerous human-centered smart-world …

Most prior work represents the shapes of point clouds by coordinates. However, it is
insufficient to describe the local geometry directly. In this paper, we present RepSurf …

Recently, directly detecting 3D objects from 3D point clouds has received increasing
attention. To extract object representation from an irregular point cloud, existing methods …

Point cloud analysis is very challenging, as the shape implied in irregular points is difficult to
capture. In this paper, we propose RS-CNN, namely, Relation-Shape Convolutional Neural …

At present, effectively aggregating and transferring the local features of point cloud is still an
unresolved technological conundrum. In this study, we propose a new space-cover …

Abstract 3D shape recognition has attracted much attention recently. Its recent advances
advocate the usage of deep features and achieve the state-of-the-art performance. However …

Point cloud processing is very challenging, as the diverse shapes formed by irregular points
are often indistinguishable. A thorough grasp of the elusive shape requires sufficiently …

Recent advances of network architecture for point cloud processing are mainly driven by
new designs of local aggregation operators. However, the impact of these operators to …

Transformers have shown superior performance on various computer vision tasks with their
capabilities to capture long-range dependencies. Despite the success, it is challenging to …

With the development of web technology, multi-modal or multi-view data has surged as a
major stream for big data, where each modal/view encodes individual property of data …