Reducing the amortization gap in end-to-end machine learning image compression

Abstract

Systems, methods, and instrumentalities are disclosed herein for reducing the amortization gap in end-to-end image compression and/or video compression. In examples, a video decoder may obtain an entropy model indication in video data. Based on the entropy model indication, the decoder may determine an entropy model to use for decoding a current picture. The current picture may be decoded based on the determined entropy model. In examples, the entropy model indication may indicate whether to use an updated entropy model or a prior entropy model for decoding the current picture. In examples, the entropy model indication may indicate an updated entropy model or a learned entropy model to use for decoding the current picture.

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