Deep structured features for semantic segmentation. - Michael Tschannen; Lukas Cavigelli; Fabian Mentzer; Thomas Wiatowski; Luca Benini (EUSIPCO, 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 (NIPS, 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)

Extreme Learned Image Compression with GANs. - Eirikur Agustsson; Michael Tschannen; Fabian Mentzer; Radu Timofte; Luc Van Gool (CVPR Workshops, 2018)

Conditional Probability Models for Deep Image Compression. - Fabian Mentzer; Eirikur Agustsson; Michael Tschannen; Radu Timofte; Luc Van Gool (CVPR, 2018)

Towards Image Understanding from Deep Compression Without Decoding. - Robert Torfason; Fabian Mentzer; Eirikur Agustsson; Michael Tschannen; Radu Timofte; Luc Van Gool (ICLR (Poster), 2018)

Practical Full Resolution Learned Lossless Image Compression. - Fabian Mentzer; Eirikur Agustsson; Michael Tschannen; Radu Timofte; Luc Van Gool (CVPR, 2019)

Generative Adversarial Networks for Extreme Learned Image Compression. - Eirikur Agustsson; Michael Tschannen; Fabian Mentzer; Radu Timofte; Luc Van Gool (ICCV, 2019)

Learning Better Lossless Compression Using Lossy Compression. - Fabian Mentzer; Luc Van Gool; Michael Tschannen (CVPR, 2020)

Learning for Video Compression With Hierarchical Quality and Recurrent Enhancement. - Ren Yang; Fabian Mentzer; Luc Van Gool; Radu Timofte (CVPR, 2020)

High-Fidelity Generative Image Compression. - Fabian Mentzer; George Toderici; Michael Tschannen; Eirikur Agustsson (NeurIPS, 2020)

Towards Generative Video Compression. - Fabian Mentzer; Eirikur Agustsson; Johannes Ballé; David Minnen; Nick Johnston; George Toderici (CoRR, 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)

Neural Image Compression: Lossy and Lossless Algorithms. - Fabian Mentzer (2021)

Neural Video Compression Using GANs for Detail Synthesis and Propagation. - Fabian Mentzer; Eirikur Agustsson; Johannes Ballé; David Minnen; Nick Johnston; George Toderici (ECCV (26), 2022)

VCT: A Video Compression Transformer. - Fabian Mentzer; George Toderici; David Minnen; Sergi Caelles; Sung Jin Hwang; Mario Lucic; Eirikur Agustsson (NeurIPS, 2022)

Lossy Compression with Gaussian Diffusion. - Lucas Theis; Tim Salimans; Matthew D. Hoffman; Fabian Mentzer (CoRR, 2022)

Multi-Realism Image Compression with a Conditional Generator. - Eirikur Agustsson; David Minnen; George Toderici; Fabian Mentzer (CVPR, 2023)

M2T: Masking Transformers Twice for Faster Decoding. - Fabian Mentzer; Eirikur Agustsson; Michael Tschannen (ICCV, 2023)

High-Fidelity Image Compression with Score-based Generative Models. - Emiel Hoogeboom; Eirikur Agustsson; Fabian Mentzer; Luca Versari; George Toderici; Lucas Theis (CoRR, 2023)

GIVT: Generative Infinite-Vocabulary Transformers. - Michael Tschannen; Cian Eastwood; Fabian Mentzer (ECCV (57), 2024)

Finite Scalar Quantization: VQ-VAE Made Simple. - Fabian Mentzer; David Minnen; Eirikur Agustsson; Michael Tschannen (ICLR, 2024)