Deep positional and relational feature learning for rotation-invariant point cloud analysis
In this paper we propose a rotation-invariant deep network for point clouds analysis. Point-
based deep networks are commonly designed to recognize roughly aligned 3D shapes …
based deep networks are commonly designed to recognize roughly aligned 3D shapes …
Robust point cloud processing through positional embedding
End-to-end trained per-point embeddings are an essential ingredient of any state-of-the-art
3D point cloud processing such as detection or alignment. Methods like PointNet [17], or the …
3D point cloud processing such as detection or alignment. Methods like PointNet [17], or the …
Unsupervised discovery of 3D structural elements for scanned indoor scenes
This paper addresses the growing demand for effective 3D sensing applications by
presenting a comprehensive point cloud segmentation method developed for large indoor …
presenting a comprehensive point cloud segmentation method developed for large indoor …
Robust registration and learning using multi-radii spherical polar Fourier transform
This paper presents effective methods using spherical polar Fourier transform data for two
different applications, with active areas of research, one as a conventional volumetric …
different applications, with active areas of research, one as a conventional volumetric …
Robust object classification approach using spherical harmonics
Point clouds produced by either 3D scanners or multi-view images are often imperfect and
contain noise or outliers. This paper presents an end-to-end robust spherical harmonics …
contain noise or outliers. This paper presents an end-to-end robust spherical harmonics …
[HTML][HTML] Robust pooling through the data mode
The task of learning from point cloud data is always challenging due to the often occurrence
of noise and outliers in the data. Such data inaccuracies can significantly influence the …
of noise and outliers in the data. Such data inaccuracies can significantly influence the …
A Novel 3D Facial Recognition for Digital Payments
KC Prabu Shankar, M Hema - … Conference on Recent Trends in Computing …, 2022 - Springer
In this research paper, we propose a system that envisions to revolutionize the way digital
payments work across the globe. With over six-hundred million users transacting regularly in …
payments work across the globe. With over six-hundred million users transacting regularly in …
[PDF][PDF] IMPLEMENTACIÓN DE UN ALGORITMO DE APRENDIZAJE MÁQUINA PARA CLASIFICAR UNA NUBE DE PUNTOS DE UN MODELO ARQUITECTÓNICO
LICEMM SILVA - 2023 - jivg.org
En este trabajo se propusó la clasificación de una nube de puntos de una pieza
arquitectónica de valor cultural que estuviera incompleta por algún tipo de daño. El estudio …
arquitectónica de valor cultural que estuviera incompleta por algún tipo de daño. El estudio …
[PDF][PDF] Robust Object Classification Approach Using Spherical Harmonics
R HOSEINNEZHAD, A BAB-HADIASHAR - academia.edu
Point clouds produced by either 3D scanners or multi-view images are often imperfect and
contain noise or outliers. This paper presents an end-to-end robust spherical harmonics …
contain noise or outliers. This paper presents an end-to-end robust spherical harmonics …