面向机器的视频编码文献：最新研究概述

近年来，深度学习技术在视频编码领域取得了显著进展，涌现出一批面向机器的视频编码文献。以下是一些重要研究成果：

'Deep Video Compression: End-to-End Learning and Coding with Convolutional Neural Networks' by Shuchang Zhou, Yuxin Wu, and Dahua Lin.
'Learning Video Compression with Recurrent Auto-Encoder Networks' by Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, and Luc Van Gool.
'End-to-End Optimized Image Compression with Generative Adversarial Networks' by Johannes Ballé, Valero Laparra, and Eero P. Simoncelli.
'Multi-View Video Coding Using Deep Neural Networks' by Dan Xu and Wenjun Zeng.
'A Deep Learning Approach to Video Compression' by George Toderici, Damien Vincent, Nick Johnston, Sung Jin Hwang, David Minnen, Joel Shor, and Michele Covell.
'Video Coding with Deep Reinforcement Learning' by Doron Shaked, Liron Yatziv, and Guillermo Sapiro.
'Learning to Compress Video with Deep Neural Networks' by Eirikur Agustsson, Fabian Mentzer, Michael Tschannen, Radu Timofte, and Luc Van Gool.
'End-to-End Training of Deep Video Compression Models' by Chen Chen, Shuo Pang, Jianfei Cai, and Xiaoping Lai.
'Deep Learning-Based Video Coding Using Convolutional Neural Networks' by Hui Su, Wenhan Yang, and Kui Liu.
'Deep Learning for Video Compression: A Review' by Wenhao Jiang, Xiaohu Guo, and Jingning Han.

这些文献涵盖了深度学习、卷积神经网络、递归自编码器、生成对抗网络等多种方法，为研究人员提供了对该领域的全面了解。