As 3D point cloud analysis has received increasing attention, the insufficient scale of point
cloud datasets and the weak generalization ability of networks become prominent. In this …

Rigid transformation poses a big challenge for many deep learning models on 3D point
clouds as the point coordinates can be drastically changed. To tackle this issue, we …

The individual identification of pigs is the basis for precision livestock farming (PLF), which
can provide prerequisites for personalized feeding, disease monitoring, growth condition …

3D object classification is an important task in computer vision. In order to explore the high-
order and multi-modal correlations among 3D data, we propose an adaptive multi …

Purpose The purpose of this study is to solve the problem of an unknown initial position in a
multi-robot raster map fusion. The method includes two-dimensional (2D) raster maps and …

Abstract 3D point cloud registration is a computational process that aligns two 3D point
clouds through transformation. ie finding matching translation and rotation. Existing state-of …

The semantic instance segmentation task on 3D data has made great progress. However,
for unstructured 3D point cloud data, the mining of regional knowledge and explicit …

Point clouds have evolved into one of the most important data formats for 3D representation.
It is becoming more popular as a result of the increasing affordability of acquisition …

Traditional methods of classification and retrieval for non-rigid 3D models, such as
topological structure-based methods and spectral analysis-based methods, high rely on …

Scene understanding is a core problem for autonomous navigation. However, its
implementation is frustrated by a variety of unsettled issues, such as understanding winding …