78 citations · 193 across the 14 of their papers we have counts for
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eess.IV2022★ 30 cited
Lossy Image Compression with Conditional Diffusion Models
Ruihan Yang, Stephan Mandt
This paper outlines an end-to-end optimized lossy image compression framework using diffusion generative models. The approach relies on the transform coding paradigm, where an imag…
eess.IV2021
Insights from Generative Modeling for Neural Video Compression
Ruihan Yang, Yibo Yang, Joseph Marino +1
While recent machine learning research has revealed connections between deep generative models such as VAEs and rate-distortion losses used in learned compression, most of this wor…
eess.IV2020★ 6 cited
Hierarchical Autoregressive Modeling for Neural Video Compression
Ruihan Yang, Yibo Yang, Joseph Marino +1
Recent work by Marino et al. (2020) showed improved performance in sequential density estimation by combining masked autoregressive flows with hierarchical latent variable models.…