Publications with the keyword "compression"

L. Theis
What makes an image realistic?
Proceedings of the 41st International Conference on Machine Learning, 2024
#perceptual quality #realism #compression #generative modeling #outlier detection
URL RIS BibTex
H. Kim, M. Bauer, L. Theis, J. R. Schwarz, and E. Dupont
C3: High-performance and low-complexity neural compression from a single image or video
Computer Vision and Pattern Recognition, 2024
#compression
Code URL Project RIS BibTex
E. Hoogeboom, E. Agustsson, F. Mentzer, L. Versari, G. Toderici, and L. Theis
High-Fidelity Image Compression with Score-based Generative Models
arXiv:2305.18231, 2023
#compression #diffusion #rectified flow
URL Files RIS BibTex
G. Flamich and L. Theis
Adaptive Greedy Rejection Sampling
IEEE International Symposium on Information Theory, 2023
#channel simulation #compression #information theory
URL PDF RIS BibTex
Y. Yang, S. Mandt, and L. Theis
An Introduction to Neural Data Compression
Foundations and Trends in Computer Graphics and Vision, 15(2), 113-200, 2023
#compression
URL PDF RIS BibTex
L. Theis, T. Salimans, M. D. Hoffman, and F. Mentzer
Lossy Compression with Gaussian Diffusion
arXiv:2206.08889, 2022
#compression #diffusion #channel simulation
URL RIS BibTex
A. Shah, W.-N. Chen, J. Balle, P. Kairouz, and L. Theis
Optimal Compression of Locally Differentially Private Mechanisms
Artificial Intelligence and Statistics, 2022
#differential privacy #compression #channel simulation
Code URL RIS BibTex
L. Theis and N. Yosri
Algorithms for the Communication of Samples
Proceedings of the 39th International Conference on Machine Learning, 2022
#compression #information theory #channel simulation
Code URL PDF RIS BibTex
L. Theis and J. Ho
Importance weighted compression
Neural Compression Workshop at ICLR, 2021
#compression #deep learning #bits back
URL RIS BibTex
L. Theis and A. B. Wagner
A coding theorem for the rate-distortion-perception function
Neural Compression Workshop at ICLR, 2021
#compression #information theory #perceptual quality
URL RIS BibTex
L. Theis and E. Agustsson
On the advantages of stochastic encoders
Neural Compression Workshop at ICLR, 2021
#compression #information theory
URL RIS BibTex
E. Agustsson and L. Theis
Universally Quantized Neural Compression
Advances in Neural Information Processing Systems 33, 2020
#compression #deep learning #channel simulation
URL PDF Appendix RIS BibTex
K. Storrs, S. V. Leuven, S. Kojder, L. Theis, and F. Huszár
Adaptive Paired-Comparison Method for Subjective Video Quality Assessment on Mobile Devices
Picture Coding Symposium, 2018
#compression #perceptual quality #psychophysics
URL Blog RIS BibTex
L. Theis, W. Shi, A. Cunningham, and F. Huszár
Lossy Image Compression with Compressive Autoencoders
International Conference on Learning Representations, 2017
#compression #deep learning
URL PDF Poster Files RIS BibTex