End-to-End Learnable Multi-Scale Feature Compression for VCM

• Published in: IEEE transactions on circuits and systems for video technology Vol. 34; no. 5; pp. 3156 - 3167
• Main Authors: Kim, Yeongwoong, Jeong, Hyewon, Yu, Janghyun, Kim, Younhee, Lee, Jooyoung, Jeong, Se Yoon, Kim, Hui Yong
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Coders; Coding; Decoding; Encoding; feature compression; Feature extraction; Image coding; Image compression; Image reconstruction; learned image compression; Lightweight; Machine vision; MPEG encoders; Object recognition; Redundancy; Task analysis; Transform coding; versatile video coding (VVC); Video coding for machine (VCM); Video compression; Vision systems; Weight reduction

The proliferation of deep learning-based machine vision applications has given rise to a new type of compression, so called video coding for machine (VCM). VCM differs from traditional video coding in that it is optimized for machine vision performance instead of human visual quality. In the feature...