CNN-Optimized Image Compression with Uncertainty based Resource Allocation

Zhenzhong Chen, Yiming Li, Feiyang Liu, Zizheng Liu, Xiang Pan, Wanjie Sun, Yingbin Wang, Yan Zhou, Han Zhu, Shan Liu

Abstract: In this paper, we provide the description of our approach designed for participating the CVPR 2018 Challenge on Learned Image Compression (CLIC). Our approach is a hybrid image coder based on CNN-optimized in-loop filter and mode coding, with uncertainty based resource allocation for compressing the task images. Two solutions were submitted, i.e., "iipTiramisu" and its speedup version "iip-TiramisuS", resulting in 32.14 dB and 32.06 dB in PSNR, respectively. These two results have been ranked No. 1 and 2 on the leaderboard.