专题演讲嘉宾:Meng-Ping Kao 高孟平

字节跳动视频架构技术专家

Meng-Ping Kao earned his Ph.D. from University of California, San Diego, where his thesis was titled “A Block-Based Scalable Motion Model for Highly Scalable Video Coding.” He received the B.S. and M.S. degrees from National Taiwan University. In 2020, he joined ByteDance and is currently leading the RTC Video Team to provide better experiences for Douyin video call and Feishu video conferencing.
Prior to joining ByteDance, Dr. Kao had been Principal Contributor/Technical Lead for several renowned video products, including Apple FaceTime and iTunes, Qualcomm Snapdragon Video SoC, and Tencent Liying Cloud Service.

高孟平,获得国立台湾大学理学学士学位与理学硕士学位、加州大学圣地牙哥分校电脑电机博士学位,研究领域主要在视频编解码的 Scalable Video Coding (SVC)。2020 年加入字节跳动,目前带领 RTC 视频团队,为抖音视频通话和飞书视频会议提供更好的体验。
在加入字节之前,高博士曾担任多个知名视频产品的首席贡献者/技术主管,包括苹果 FaceTime 和 iTunes、高通骁龙视频 SoC 和腾讯丽影云服务。

by Meng-Ping Kao 高孟平

字节跳动
视频架构技术专家

Outline: 
1. Common RTC Pub-Sub Joint Optimization Techniques - Up/Down Bandwidth Estimation 
2. More on Pub-Sub Joint Optimization Explorations 

  • Performance Optimization Framework for Video Super-Resolution 
  • Latency Optimization for Content-Adaptive Screen Sharing 
  • Adaptive Referencing Scheme for Extremely Volatile Networks 

3. Future Work and Challenges

演讲提纲: 
1. 传统 RTC 上下行联动技术 - 带宽探测 
2. 真端到端上下行联动优化实践 

  • 超分辩率的性能迭代优化框架 
  • 智能内容模式的下行延时优化 
  • 智能参考帧的极致弱网延时体验 

3. 视频端到端优化技术的未来展望 

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北京·四季酒店

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