Fabian Mentzer

According to our database, Fabian Mentzer authored at least 22 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Finite Scalar Quantization: VQ-VAE Made Simple.

Fabian Mentzer, David Minnen, Eirikur Agustsson, Michael Tschannen

Proceedings of the Twelfth International Conference on Learning Representations, 2024

GIVT: Generative Infinite-Vocabulary Transformers.

Michael Tschannen, Cian Eastwood, Fabian Mentzer

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

High-Fidelity Image Compression with Score-based Generative Models.

Emiel Hoogeboom, Eirikur Agustsson, Fabian Mentzer, Luca Versari, George Toderici, Lucas Theis

CoRR, 2023

M2T: Masking Transformers Twice for Faster Decoding.

Fabian Mentzer, Eirikur Agustsson, Michael Tschannen

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Multi-Realism Image Compression with a Conditional Generator.

Eirikur Agustsson, David Minnen, George Toderici, Fabian Mentzer

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Lossy Compression with Gaussian Diffusion.

Lucas Theis, Tim Salimans, Matthew D. Hoffman, Fabian Mentzer

CoRR, 2022

VCT: A Video Compression Transformer.

Fabian Mentzer, George Toderici, David Minnen, Sergi Caelles, Sung Jin Hwang, Mario Lucic, Eirikur Agustsson

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Neural Video Compression Using GANs for Detail Synthesis and Propagation.

Fabian Mentzer, Eirikur Agustsson, Johannes Ballé, David Minnen, Nick Johnston, George Toderici

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Neural Image Compression: Lossy and Lossless Algorithms.

Fabian Mentzer

PhD thesis, 2021

Learning for Video Compression With Recurrent Auto-Encoder and Recurrent Probability Model.

Ren Yang, Fabian Mentzer, Luc Van Gool, Radu Timofte

IEEE J. Sel. Top. Signal Process., 2021

Towards Generative Video Compression.

Fabian Mentzer, Eirikur Agustsson, Johannes Ballé, David Minnen, Nick Johnston, George Toderici

CoRR, 2021

2020

High-Fidelity Generative Image Compression.

Fabian Mentzer, George Toderici, Michael Tschannen, Eirikur Agustsson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning for Video Compression With Hierarchical Quality and Recurrent Enhancement.

Ren Yang, Fabian Mentzer, Luc Van Gool, Radu Timofte

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Learning Better Lossless Compression Using Lossy Compression.

Fabian Mentzer, Luc Van Gool, Michael Tschannen

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Generative Adversarial Networks for Extreme Learned Image Compression.

Eirikur Agustsson, Michael Tschannen, Fabian Mentzer, Radu Timofte, Luc Van Gool

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Practical Full Resolution Learned Lossless Image Compression.

Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Towards Image Understanding from Deep Compression Without Decoding.

Robert Torfason, Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool

Proceedings of the 6th International Conference on Learning Representations, 2018

Conditional Probability Models for Deep Image Compression.

Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Extreme Learned Image Compression with GANs.

Eirikur Agustsson, Michael Tschannen, Fabian Mentzer, Radu Timofte, Luc Van Gool

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

2017

Soft-to-Hard Vector Quantization for End-to-End Learned Compression of Images and Neural Networks.

Eirikur Agustsson, Fabian Mentzer, Michael Tschannen, Lukas Cavigelli, Radu Timofte, Luca Benini, Luc Van Gool

CoRR, 2017

Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations.

Eirikur Agustsson, Fabian Mentzer, Michael Tschannen, Lukas Cavigelli, Radu Timofte, Luca Benini, Luc Van Gool

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Deep structured features for semantic segmentation.

Michael Tschannen, Lukas Cavigelli, Fabian Mentzer, Thomas Wiatowski, Luca Benini

Proceedings of the 25th European Signal Processing Conference, 2017