Exploring Invertibility in Image Processing and Restoration

Speaker: Dr. Qifeng CHEN
         Assistant Professor
         Department of Computer Science and Engineering
         Hong Kong University of Science and Technology

Title:  "Exploring Invertibility in Image Processing and Restoration"

Date:   Monday, 21 March 2022

Time:   4:00pm - 5:00pm (HKT)

Zoom link:
https://hkust.zoom.us/j/928308079?pwd=MW9wTCtlSDd2MnViZGdNd2oreUpXZz09

Meeting ID:     928 308 079
Passcode:       20212022

Abstract:

Today's smartphones have enabled numerous stunning visual effects from
denoising to beautification, and we can share high-quality JPEG images
easily on the internet, but it is still valuable for photographers and
researchers to keep the original raw camera data for further
post-processing (e.g., retouching) and analysis. However, the huge size of
raw data hinders its popularity in practice, so can we almost perfectly
restore the raw data from a compressed RGB image and thus avoid storing
any raw data? This question leads us to design an invertible image signal
processing pipeline. Then we further explore invertibility in other image
processing and restoration tasks, including image compression, reversible
image conversion (e.g., image-to-video conversion), embedding novel views
in a single JPEG image. In the end, we demonstrate a general framework for
restorable image processing operators with quasi-invertible networks.


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Biography:

Qifeng Chen is an assistant professor at The Hong Kong University of
Science and Technology. He received his PhD. in computer science from
Stanford University in 2017. His research interests include image
processing and synthesis, 3D vision, and autonomous driving. He was named
one of 35 Innovators under 35 in China by MIT Technology Review and
received the Google Faculty Research Award in 2018. He won 2nd place
worldwide at the ACM-ICPC World Finals and a gold medal in IOI. He
co-founded the startups Lino and DeepMirror.