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About My SELF
About My SELF
Samsung AI Center
Ph.D. in Electrical Engineering in KAIST
E-mail: dkfzkvk1992@gmail.com
[CV] [Google Scholar] [LinkedIn] [Github]
Research Interests
Research Interests
LLM/MMFM
AI Agent
Image Quality Assessment
Knowledge Distillation
Image Perceptual Quality Enhancement
PUblications
PUblications
ATTIQA: Generalizable Image Quality Feature Extractor using Attribute-aware Pretraining
D Kwon, D Kim, S Ki, Y Jo, HE Lee, SJ Kim
ACCV 2024
[PDF]
Information-theoretic gan compression with variational energy-based model
M Kang, H Yoo, E Kang, S Ki, HE Lee, B Han
NeurIPS 2022
[PDF]
A Novel Just-Noticeable-Difference-based Saliency-Channel Attention Residual Network for Full-Reference Image Quality Predictions
Soomin Seo*, Sehwan Ki*, and Munchurl Kim (*equal contribution)
IEEE Transactions on Circuits and Systems for Video Technology, Early Access, Oct. 2020
[PDF]
High-Resolution Image Dehazing with respect to Training Losses and Receptive Field Sizes
Hyeonjun Sim, Sehwan Ki, and Munchurl Kim
Computer Vision and Pattern Recognition Workshops (CVPRW), 2018 IEEE Conference on, Salt Lake CIty, UT, USA, 18 June 2018.
(Oral Presentation, 2nd Rank in Outdoor Track)
Fully End-to-End learning based Conditional Boundary Equilibrium GAN with Receptive Field Sizes Enlarged for Single Ultra-High Resolution Image Dehazing
Sehwan Ki, Hyeonjun Sim, and Munchurl Kim
Computer Vision and Pattern Recognition Workshops (CVPRW), 2018 IEEE Conference on, Salt Lake CIty, UT, USA, 18 June 2018.
(4th Rank in Indoor Track)
NTIRE 2018 Challenge on Image Dehazing: Methods and Results
Cosmin Ancuti, Codruta O. Ancuti, Radu Timofte, Luc Van Gool, Lei Zhang, Ming-Hsuan Yang [and 59 others, including Sehwan Ki]
Computer Vision and Pattern Recognition Workshops (CVPRW), 2018 IEEE Conference on, Salt Lake CIty, UT, USA, 18 June 2018.
[PDF]
NTIRE 2018 Challenge on Single Image Super-Resolution: Methods and Results
Radu Timofte, Shuhang Gu, Jiqing Wu, Luc Van Gool, Lei Zhang, Ming-Hsuan Yang [and 95 others, including Sehwan Ki]
Computer Vision and Pattern Recognition Workshops (CVPRW), 2018 IEEE Conference on, Salt Lake CIty, UT, USA, 18 June 2018.
[PDF]
Domestic Journal
Domestic Journal
Sehwan Ki, Dae-eun Kim and Munchurl Kim, “Performance Analysis of Super-Resolution based Video Coding for HEVC,” Journal of Broadcast Engineering, vol. 24, no. 2, pp. 306-314, Mar 2019.
Dae-eun Kim, Sehwan Ki and Munchurl Kim, “Scalable Video Coding using Super-Resolution based on Convolutional Neural Networks for Video Transmission over Very Narrow-Bandwidth Networks,” Journal of Broadcast Engineering, vol. 24, no. 1, pp. 132-141, Jan 2019.
Domestic Conference
Domestic Conference
Sehwan Ki and Munchurl Kim, “Content-Adaptive Model Update of Convolutional Neural Networks for Super-Resolution”, Korea Institute of Broadcast and Media Engineers Workshop, Nov. 2020.
Sehwan Ki and Munchurl Kim, “Temporally adaptive and region- selective signaling of applying multiple neural network models”, Korea Institute of Broadcast and Media Engineers Workshop, Nov. 2020.
Sehwan Ki and Munchurl Kim, “A Study on the Convolution Neural Network based on Blind High Dynamic Range Image Quality Assessment,” Korea Institute of Communications and Information Sciences Workshop, Dec. 2018.
Sehwan Ki, Jae-seok Choi, Sooye Kim and Munchurl Kim, “Accelerating Deep Learning based Super-resolution algorithm using GPU,” Korea Institute of Broadcast and Media Engineers Workshop, June 2017.
Sehwan Ki and Munchurl Kim, “Just Noticeable Quantization Blur model on the DCT complexity feature of the image,” Korea Institute of Broadcast and Media Engineers Workshop, June 2016.
Sehwan Ki and Munchurl Kim, “JND based Video Preprocessing Adaptive to Quantization Step sizes for Perceptual Redundancy Reduction,” Korea Institute of Broadcast and Media Engineers Workshop, Sept. 2016.
PAtent and Standard
PAtent and Standard
IMAGE PROCESSING METHOD AND APPARATUS USING SELECTION UNIT, 1021537860000 (2020.09.02)
VIDEO PROCESSING METHOD AND APPARATUS, 1023646280000 (2022.02.15)
METHOD AND DEVICE FOR MAGE QUALITY ENHANCEMENT USING MULTIPLE MODELS OF VARIOUS MAGE SIGNAL CHARACTERISTICS, 1026420590000 (2024.02.26)
NEURAL NETWORK PROCESSING METHOD AND APPARATUS USING TEMPORALLY ADAPTIVE, REGION-SELECTIVE SIGNALING, 1026420580000 (2024.02.26)
Sehwan Ki and Munchurl Kim, “Use cases and requirements for neural network compression for multimedia content description and analysis ,” ISO/IEC JTC1/SC29/WG11/N18731, July 2019, Gothenburg, SE. [PDF]
Awards and Honors
Awards and Honors
NTIRE 2018 Challenge on Single Image Dehazing in conjunction with CVPR 2018, 4th Place Award, June 2018 [PDF]
NTIRE 2018 Challenge on Single Image Super-Resolution in conjunction with CVPR 2018, Honorable Mention Award, June 2018 [PDF]
Kyungpook National University, Excellence Graduate Honor (3/395) , Feb. 2015
2014 KNU Capstone Design Contest 2nd Place Award, Dec. 2014
Education
Education
Ph.D. in Electrical Engineering, KAIST, Daejeon, Korea, Mar. 2017 - Feb. 2021 (GPA: 4.13/4.30)
M.S. in Electrical Engineering, KAIST, Daejeon, Korea, Mar. 2015 - Feb. 2017 (GPA: 4.12/4.30)
B.S. in Electrical Engineering, Kyungpook, Daegu, Korea, Mar. 2011 - Feb. 2015 (GPA: 4.15/4.30)
Major Skills
Major Skills
Programming Languages - C, C++, Matlab, Python, CUDA C, OpenGL/CL, SNPE
Deep Learning Framework - Pytorch, Tensorflow
Subjective Video and Image Quality Assessment
GPU Programming
Deep learning for Mobile Devices
Project Experience
Project Experience
National Research Foundation of Korea, Research Project on Intelligent and Highly Realistic Visual Processing for Smart Broadcasting Media (Super-Resolution, Dehazing, Deep Learning based image/video quality enhancement), Mar. 2017 – Dec. 2020
LG, Low complexity deep Learning based super-resolution. Dec. 2018 - Dec. 2019
ETRI, Deep Learning based New Generation Video Coding. Mar. 2016 - Dec. 2019
LIG Nexone, Deep Learning based Ultra-narrow bandwidth Video Coding, Super-Resolution. Jan. 2018 - Dec. 2019
Huawei Technologies Co. Ltd., Deep Learning based Reconstructed Video Coding, GPU programming. Apr. 2017 - Nov. 2019
Huawei Technologies Co. Ltd., Deep Learning based Super-Resolution, GPU programming. Sept. 2016 - Mar. 2017
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