49 citations · 62 across the 2 of their papers we have counts for
6 papers · 1 filter
High-Fidelity Image Compression with Score-based Generative Models
Emiel Hoogeboom, Eirikur Agustsson, Fabian Mentzer +3
Despite the tremendous success of diffusion generative models in text-to-image generation, replicating this success in the domain of image compression has proven difficult. In this…
M2T: Masking Transformers Twice for Faster Decoding
Fabian Mentzer, Eirikur Agustsson, Michael Tschannen
We show how bidirectional transformers trained for masked token prediction can be applied to neural image compression to achieve state-of-the-art results. Such models were previous…
Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model
Ren Yang, Fabian Mentzer, Luc Van Gool +1
The past few years have witnessed increasing interests in applying deep learning to video compression. However, the existing approaches compress a video frame with only a few numbe…
High-Fidelity Generative Image Compression
Fabian Mentzer, George Toderici, Michael Tschannen +1
We extensively study how to combine Generative Adversarial Networks and learned compression to obtain a state-of-the-art generative lossy compression system. In particular, we inve…
Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement
Ren Yang, Fabian Mentzer, Luc Van Gool +1
In this paper, we propose a Hierarchical Learned Video Compression (HLVC) method with three hierarchical quality layers and a recurrent enhancement network. The frames in the first…
Practical Full Resolution Learned Lossless Image Compression
Fabian Mentzer, Eirikur Agustsson, Michael Tschannen +2
We propose the first practical learned lossless image compression system, L3C, and show that it outperforms the popular engineered codecs, PNG, WebP and JPEG 2000. At the core of o…