9 citations · 17 across the 3 of their papers we have counts for
5 papers
Efficient Adaptation of Neural Network Filter for Video Compression
Yat-Hong Lam, Alireza Zare, Francesco Cricri +2
We present an efficient finetuning methodology for neural-network filters which are applied as a postprocessing artifact-removal step in video coding pipelines. The fine-tuning is…
End-to-End Learning for Video Frame Compression with Self-Attention
Nannan Zou, Honglei Zhang, Francesco Cricri +5
One of the core components of conventional (i.e., non-learned) video codecs consists of predicting a frame from a previously-decoded frame, by leveraging temporal correlations. In…
Compressing Weight-updates for Image Artifacts Removal Neural Networks
Yat Hong Lam, Alireza Zare, Caglar Aytekin +4
In this paper, we present a novel approach for fine-tuning a decoder-side neural network in the context of image compression, such that the weight-updates are better compressible.…
A Compression Objective and a Cycle Loss for Neural Image Compression
Caglar Aytekin, Francesco Cricri, Antti Hallapuro +3
In this manuscript we propose two objective terms for neural image compression: a compression objective and a cycle loss. These terms are applied on the encoder output of an autoen…
Block-optimized Variable Bit Rate Neural Image Compression
Caglar Aytekin, Xingyang Ni, Francesco Cricri +3
In this work, we propose an end-to-end block-based auto-encoder system for image compression. We introduce novel contributions to neural-network based image compression, mainly in…