We present an exciting journey from 3D point‐cloud data (PCD) to the state of the art in
graph neural networks (GNNs) and their evolution with explainable artificial intelligence …

Text-to-3D generation is to craft a 3D object according to a natural language description.
This can significantly reduce the workload for manually designing 3D models and provide a …

Point cloud completion is the task of producing a complete 3D shape given an input of a
partial point cloud. It has become a vital process in 3D computer graphics, vision and …

In the realm of robotic grasping, achieving accurate and reliable interactions with the
environment is a pivotal challenge. Traditional methods of grasp planning methods utilizing …

We present a 3D scene completion method that recovers the complete geometry of multiple
unseen objects in complex scenes from a single RGB-D image. Despite notable …

Robotic manipulation is critical for admitting robotic agents to various application domains,
like intelligent assistance. A major challenge therein is the effective 6DoF grasping of …

This work presents a new completion method that specifically designed for low-overlapping
partial point cloud registration. Based on the assumption that the candidate partial point …

In term of the industrialization era, robot gradually appears in some production stages
instead of worker. There is an irreversible tendency to deploy the image processing …

Recovering the complete structure from partial point clouds in arbitrary poses is challenging.
Recently, many efforts have been made to address this problem by developing SO (3) …

We propose a novel pipeline for unknown object grasping in shared robotic autonomy
scenarios. State-of-the-art methods for fully autonomous scenarios are typically learning …