ICML 2023

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Poster

I$^2$SB: Image-to-Image Schrödinger Bridge

Guan-Horng Liu · Arash Vahdat · De-An Huang · Evangelos Theodorou · Weili Nie · Anima Anandkumar

Wed Jul 26 05:00 PM -- 06:30 PM (PDT) @ Exhibit Hall 1 #705

in Poster Session 4 »

We propose Image-to-Image Schrödinger Bridge (I$^2$SB), a new class of conditional diffusion models that directly learn the nonlinear diffusion processes between two given distributions. These diffusion bridges are particularly useful for image restoration, as the degraded images are structurally informative priors for reconstructing the clean images. I$^2$SB belongs to a tractable class of Schrödinger bridge, the nonlinear extension to score-based models, whose marginal distributions can be computed analytically given boundary pairs. This results in a simulation-free framework for nonlinear diffusions, where the I$^2$SB training becomes scalable by adopting practical techniques used in standard diffusion models. We validate I$^2$SB in solving various image restoration tasks, including inpainting, super-resolution, deblurring, and JPEG restoration on ImageNet 256$\times$256 and show that I$^2$SB surpasses standard conditional diffusion models with more interpretable generative processes. Moreover, I$^2$SB matches the performance of inverse methods that additionally require the knowledge of the corruption operators. Our work opens up new algorithmic opportunities for developing efficient nonlinear diffusion models on a large scale. Project page and codes: https://i2sb.github.io/

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Author Information

Guan-Horng Liu (Georgia Institute of Technology)

Arash Vahdat (NVIDIA Research)

De-An Huang (NVIDIA)

Evangelos Theodorou (Georgia Tech)

Weili Nie (NVIDIA)

Anima Anandkumar (Caltech and NVIDIA)

Anima Anandkumar is a Bren Professor at Caltech and Director of ML Research at NVIDIA. She was previously a Principal Scientist at Amazon Web Services. She is passionate about designing principled AI algorithms and applying them to interdisciplinary domains. She has received several honors such as the IEEE fellowship, Alfred. P. Sloan Fellowship, NSF Career Award, Young investigator awards from DoD, Venturebeat’s “women in AI” award, NYTimes GoodTech award, and Faculty Fellowships from Microsoft, Google, Facebook, and Adobe. She is part of the World Economic Forum's Expert Network. She has appeared in the PBS Frontline documentary on the “Amazon empire” and has given keynotes in many forums such as the TEDx, KDD, ICLR, and ACM. Anima received her BTech from Indian Institute of Technology Madras, her PhD from Cornell University, and did her postdoctoral research at MIT and assistant professorship at University of California Irvine.