CD: Cool-Chic Video with Decoupled Representation

Yue Li, Chaoyi Lin, Junru Li, Kai Zhang, Li Zhang

Abstract: Neural compression methods often rely on highly expressive models to fit large datasets, resulting in significant decoding complexity. Overfitted codecs have been proposed as an alternative to reduce decoding complexity. However, these approaches typically lack flexibility in encoding configurations. To address this, we introduce CD, a neural video compression method that employs picture-wise overfitting. CD is built upon the Cool-chic video framework [1], but incorporates Decoupled representations for motion and residue. Additionally, we propose an effective training strategy for CD to further enhance its performance.

External IDs:dblp:conf/dcc/LiLLZZ25b