中文版：
题目：神经视频压缩的最新进展
报告人：A. Murat Tekalp院士
工作单位：土耳其伊斯坦布尔科奇大学
报告题目：神经视频压缩的最新进展
报告时间：2022年8月16日（周二）下午16:00
报告链接：
https://teams.microsoft.com/l/meetup-join/19%3aB4gmRcUATAMA2iJqi-xXvtfPFfTbxVJPxSW_pcAPBao1%40thread.tacv2/1638719716825?context=%7b%22Tid%22%3a%2222804ebb-30d5-47df-942f-f3a3722f0225%22%2c%22Oid%22%3a%2216a60c03-ad7a-4b85-a403-8ebd947e010c%22%7d
内容摘要：
神经图像视频压缩（也称为学习图像/图像压缩）的性能超过了基于传统标准的图像视频编解码器，这是因为它可以同时对非线性变换、运动补偿和熵模型进行端到端的率失真 (R-D) 优化训练。数据驱动的深度学习方法更深层的好处是神经模型可以针对任何可微的损失函数进行优化，包括视觉感知损失函数，从而进行感知图像视频压缩，这是传统编解码器无法轻松处理的。本报告将首先介绍学习图像视频压缩的基本原理和近期进展，包括运动补偿模型、流残差编码、条件编码、时空熵建模、多率神经模型以及率感知失真在学习图像视频编码的权衡。下一步将讨论学习视频压缩的最新技术，并介绍我们所研究的低延迟和随机访问编解码器配置的最新结果，包括分层双向视频压缩工作，它结合了分层双向运动补偿和端到端率失真优化的优点。
个人简介：
A. Murat Tekalp（IEEE研究员）于1984年在美国纽约州特洛伊市伦斯勒理工学院 (RPI) 获得博士学位，1984年至1987年间在纽约罗切斯特的伊士曼柯达公司工作，1987年至2005年间在罗切斯特大学工作，并被提升为杰出大学教授。A. Murat Tekalp目前是土耳其伊斯坦布尔科奇大学的教授，曾在2010年至2013年间担任工程学院院长。A. Murat Tekalp的研究方向是数字图像和视频处理，包括视频压缩和流式传输、视频网络、多视图和3-D视频处理，以及用于图像视频处理和压缩的深度学习。A. Murat Tekalp被选为土耳其科学院和欧洲科学院的成员，曾担任 IEEE 信号处理汇刊 (1990–1992) 和IEEE图像处理汇刊 (1994–1996) 的副主编，在1999年至2010年间担任由Elsevier出版的EURASIP期刊Signal Processing: Image Communications 的主编，是IEEE Signal Processing杂志 (2007-2010) 和 Proceedings of the IEEE的编辑委员会成员（2014-2020）。A. Murat Tekalp在1996年1月至1997年12月期间担任IEEE信号处理协会图像和多维信号处理技术委员会主席，于2002年被任命为美国纽约州罗切斯特市 IEEE 国际图像处理会议 (ICIP) 的总主席以及IEEE ICIP 2020和ICIP 2024技术计划联合主席，曾在欧洲研究委员会 (ERC) 高级拨款小组（2009-2015年）和启动拨款小组（2021年）中任职。A. Murat Tekalp于1995年撰写了普伦蒂斯霍尔书籍《Digital Video Processing》，该书的第二版全面重编后于2015年出版。
【编辑：王健】
英文版：
题目：Academic Report Notice of A. Murat Tekalp：Recent Advances in Neural Video Compression
Speaker: Academician A. Murat Tekalp
Title: Recent Advances in Neural Video Compression
Time: 16:00 pm, August 16, 2022 (Tuesday)
Link: https://teams.microsoft.com/l/meetup-join/19%3aB4gmRcUATAMA2iJqi-xXvtfPFfTbxVJPxSW_pcAPBao1%40thread.tacv2/1638719716825?context=%7b%22Tid%22%3a%2222804ebb-30d5-47df-942f-f3a3722f0225%22%2c%22Oid%22%3a%2216a60c03-ad7a-4b85-a403-8ebd947e010c%22%7d
Abstract:
Neural image video compression (also known as learned image/image compression) have recently exceeded the performance of traditional standards-based image video codecs. This is mainly because they allow end-to-end rate-distortion (R-D) optimized training of nonlinear transform, motion compensation and entropy models simultaneously. A further benefit of data-driven deep learning approach is that neural models can be optimized for any differentiable loss function, including visual perceptual loss functions, leading to perceptual image video compression, which cannot be easily handled by traditional codecs. This talk reviews the fundamentals of and recent advances in learned image video compression, including advances in motion-compensation models, flow residual coding, conditional coding, spatio-temporal entropy modeling, multi-rate neural models and the rate-perception-distortion tradeoff in learned image video coding. I will discuss the state-of-the-art in learned video compression and present recent results on learned low-delay and random access codec configurations, including our own work on hierarchical bi-directional video compression that combines the benefits of hierarchical bi-directional motion compensation and end-to-end rate-distortion optimization.
Personal Introduction:
A. Murat Tekalp (Fellow, IEEE) received the Ph.D. degree in electrical, computer, and systems engineering from Rensselaer Polytechnic Institute (RPI), Troy, NY, USA, in 1984. He was with Eastman Kodak Company, Rochester, New York, from 1984 to 1987, and with the University of Rochester, Rochester, New York, from 1987 to 2005, where he was promoted to Distinguished University Professor. He is currently a Professor with Koc University, Istanbul, Turkey. He served as the Dean of Engineering between 2010 and 2013. His research interests are in digital image and video processing, including video compression and streaming, video networking, multi-view and 3-D video processing, and deep learning for image video processing and compression. He has been elected a member of Turkish Academy of Sciences and Academia Europaea. He served as an Associate Editor for the IEEE Transactions on Signal Processing (1990–1992) and IEEE Transactions on Image Processing (1994–1996). He was the Editor-in-Chief for the EURASIP journal Signal Processing: Image Communication published by Elsevier between 1999 and 2010. He was on the Editorial Board for the IEEE Signal Processing Magazine (2007–2010) and the Proceedings of the IEEE (2014–2020). He chaired the IEEE Signal Processing Society Technical Committee on Image and Multidimensional Signal Processing (January 1996–December 1997). He was appointed as the General Chair of IEEE International Conference on Image Processing (ICIP), Rochester, NY, USA, in 2002 and the Technical Program Co-Chair for IEEE ICIP 2020 and ICIP 2024. He served in the European Research Council (ERC) Advanced Grant Panels (2009–2015) and Starting Grant Panel in 2021. He is currently on the Editorial Board of Wiley-IEEE Press. He has authored the Prentice Hall book Digital Video Processing (1995), a completely rewritten second edition of which is published in 2015.
[Editor: jian Wang]