由于增强现实、虚拟现实体验的日益普及，以及自动驾驶的3D传感的普及，近年来工业界和学术界对捕获高分辨率现实世界点云的兴趣显著增长。点云是一类新的非均匀稀疏信号，它对信号处理、压缩和深度学习等领域提出了独特的挑战。本次报告介绍了用于大规模点云处理的多尺度稀疏卷积学习框架，及其在几何和属性超分辨率以及具有潜在空间补偿的动态点云压缩方面的应用。该架构具有高内存效率，并且可以学习深度网络来处理实际应用中的大规模点云。初步结果表明，该框架在几何超分辨、属性块化和超分辨、动态点云序列压缩等方面取得了新的研究成果。

12月18日上午，密苏里大学的Zhu Li教授应邀来作一场主题为《Multi-Scale Sparse Conv Learning for Point Cloud Compression and Super-Resolving》的学术报告，并和科大的同学们深入讨论。

在报告中，Zhu Li教授首先介绍了点云信号与其他常见信号的差别，以及点云特殊性对点云信号处理带来的挑战。针对点云信号的特殊性，Zhu Li教授详细介绍了作为点云处理常用工具的稀疏卷积的理论原理和实现机制。进一步地，Zhu Li教授深入介绍了点云上采样、点云编码的相关工作，对这些工作的算法设计、实现框架和实验结果进行了详细的介绍。

在报告的最后，现场许多老师、同学针对报告内容提出许多问题，和Zhu Li教授积极地讨论。

Zhu Li教授简介：

Zhu Li is a professor with the Dept of Computer Science & Electrical Engineering, University of Missouri, Kansas City(UMKC), and the director of NSF I/UCRC Center for Big Learning (CBL) at UMKC. He received his PhD in Electrical & Computer Engineering from Northwestern University in 2004. He was the AFRL summer faculty at the UAV Research Center, US Air Force Academy (USAFA), 2016-18, 2020-23. He was Senior Staff Researcher with the Samsung Research America's Multimedia Standards Research Lab in Richardson, TX, 2012-2015, Senior Staff Researcher with FutureWei (Huawei) Technology's Media Lab in Bridgewater, NJ, 2010~2012, Assistant Professor with the Dept of Computing, the Hong Kong Polytechnic University from 2008 to 2010, and a Principal Staff Research Engineer with the Multimedia Research Lab (MRL), Motorola Labs, from 2000 to 2008. His research interests include point cloud and light field compression, graph signal processing and deep learning in the next gen visual compression, remote sensing, image processing and understanding. He has 50+ issued or pending patents, 200+ publications in book chapters, journals, and conferences in these areas. He is an IEEE senior member, Associate Editor-in-Chief for IEEE Trans on Circuits & System for Video Tech, 2020~, Associate Editor for IEEE Trans on Image Processing(2020~), IEEE Trans.on Multimedia (2015-18), IEEE Trans on Circuits & System for Video Technology(2016-19). He received the Best Paper Runner-up Award at the Perception Beyond Visual Spectrum (PBVS) grand challenge at CVPR 2023, Best Paper Award at IEEE Int'l Conf on Multimedia & Expo (ICME), Toronto, 2006, and IEEE Int'l Conf on Image Processing (ICIP), San Antonio, 2007.