Abstract
Image degradation is common in real-world scenarios due to factors such as transmission loss, limited camera capability, or poor shooting conditions. These issues often remove key high-frequency details, causing major performance drops in high-level vision tasks like classification, segmentation, and detection. Image restoration (IR) seeks to recover lost details in low-quality images using learned natural image priors, offering a potential solution to this problem. However, studies show that simply applying IR as a preprocessing step rarely restores the information most relevant to high-level tasks. This insight has led to Task-driven Image Restoration (TDIR), which focuses on enhancing visual quality in ways that directly benefit downstream vision tasks. In this talk, we will discuss the key challenges in TDIR and highlight several recent, efficient approaches to address them.
About the speaker
Kyoung Mu Lee (Fellow, IEEE) is currently the Editor-in-Chief (EiC) of the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI); He is a distinguished professor at Seoul National University (SNU). He was the founding director of the Interdisciplinary Graduate Program in SNU. He is an Advisory Board Member of the Computer Vision Foundation (CVF). He was a Distinguished Lecturer of the Asia-Pacific Signal and Information Processing Association (APSIPA), from 2012 to 2013. He has received several awards, in particular, the Medal of Merit and the Scientist of Engineers of the Month Award from the Korean Government, in 2018 and 2020, respectively; the Most Influential Paper Over the Decade Award by the IAPR Machine Vision Application, in 2009; the ACCV Honorable Mention Award, in 2007; the Okawa Foundation Research Grant Award, in 2006, and the SNU Excellence in Research Award in 2020. He has also served as a General Chair for ICCV2019, ACMMM2018, and ACCV2018; and an Area Chair for CVPR, ICCV, and ECCV many times. He is the founding member and served as the President of the Korean Computer Vision Society (KCVS). Prof. Lee is a Fellow of IEEE, a member of the Korean Academy of Science and Technology (KAST) and the National Academy of Engineering of Korea (NAEK).
