The second generation Audio Video Coding Standard (AVS2) is the most recent video coding standard. By introducing several new coding techniques, AVS2 can provide more efficient compression for scene videos such as surveillance videos, conference videos, etc. Due to the limited scenes, scene videos have great redundancy especially in background region. The new scene video coding techniques applied in AVS2 mainly focus on reducing redundancy in order to achieve higher compression. This paper introduces several important AVS2 scene video coding techniques. Experimental results show that with scene video coding tools, AVS2 can save nearly 40% BD-rate (Bj?ntegaard?Delta bit-rate) on scene videos.

Visual search has been a long-standing problem in applications such as location recognition and product search. Much research has been done on image representation, matching, indexing, and retrieval. Key component technologies for visual search have been developed, and numerous real-world applications are emerging. To ensure application interoperability, the Moving Picture Experts Group (MPEG) has begun standardizing visual search technologies and is developing the compact descriptors for visual search (CDVS) standard. MPEG seeks to develop a collaborative platform for evaluating existing visual search technologies. Peking University has participated in this standardization since the 94th MPEG meeting, and significant progress has been made with the various proposals. A test model (TM) has been selected to determine the basic pipeline and key components of visual search. However, the first-version TM has high computational complexity and imperfect retrieval and matching. Core experiments have therefore been set up to improve TM. In this article, we summarize key technologies for visual search and report the progress of MPEG CDVS. We discuss Peking University’s efforts in CDVS and also discuss unresolved issues.