This article presents an overview of the recent standardization activities for point cloud
compression (PCC). A point cloud is a 3D data representation used in diverse applications …

Non‐rigid registration computes an alignment between a source surface with a target
surface in a non‐rigid manner. In the past decade, with the advances in 3D sensing …

Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …

Efficiently reconstructing complex and intricate surfaces at scale is a long-standing goal in
machine perception. To address this problem we introduce Deep Local Shapes (DeepLS), a …

Recently, neural networks have been used as implicit representations for surface
reconstruction, modelling, learning, and generation. So far, training neural networks to be …

Due to the increased popularity of augmented and virtual reality experiences, the interest in
capturing the real world in multiple dimensions and in presenting it to users in an immersible …

An approximation model based on convolutional neural networks (CNNs) is proposed for
flow field predictions. The CNN is used to predict the velocity and pressure field in unseen …

Crack detection is of significant importance for concrete structural inspection. Unmanned
aerial vehicle (UAV)-based crack detection systems abound, but simply quantifying cracks …

We introduce ABC-Dataset, a collection of one million Computer-Aided Design (CAD)
models for research of geometric deep learning methods and applications. Each model is a …

Abstract We present PPFNet-Point Pair Feature NETwork for deeply learning a globally
informed 3D local feature descriptor to find correspondences in unorganized point clouds …