1 citations · 2 across the 2 of their papers we have counts for
4 papers
Boosting neural video codecs by exploiting hierarchical redundancy
Reza Pourreza, Hoang Le, Amir Said +2
In video compression, coding efficiency is improved by reusing pixels from previously decoded frames via motion and residual compensation. We define two levels of hierarchical redu…
Lossy Compression with Distortion Constrained Optimization
Ties van Rozendaal, Guillaume Sautière, Taco S. Cohen
When training end-to-end learned models for lossy compression, one has to balance the rate and distortion losses. This is typically done by manually setting a tradeoff parameter $β…
Feedback Recurrent Autoencoder for Video Compression
Adam Golinski, Reza Pourreza, Yang Yang +2
Recent advances in deep generative modeling have enabled efficient modeling of high dimensional data distributions and opened up a new horizon for solving data compression problems…
Feedback Recurrent AutoEncoder
Yang Yang, Guillaume Sautière, J. Jon Ryu +1
In this work, we propose a new recurrent autoencoder architecture, termed Feedback Recurrent AutoEncoder (FRAE), for online compression of sequential data with temporal dependency.…