Sanghyun Woo
Ph.D Candidate
Robotics and Computer Vision Lab.
Korea Advanced Institute of Science and Technology (KAIST)
shwoo93 [at] kaist.ac.kr
[CV] [Google Scholar] [Github] [LinkedIn]
Hi!
I'm Sanghyun Woo, a second-year Ph.D. student at Korea Advanced Institute of Science and Technology (KAIST), advised by Prof. In So Kweon. I earned my B.S and M.S degrees in electrical engineering from Seoul National University (SNU) and KAIST in 2017 and 2019, respectively. I was a summer research intern at Adobe (San Jose, CA) working with Joon-Young Lee in 2019. I am a recipient of Microsoft Research Asia Fellowship 2020.
Research Interests
My research aims to build an AI agent that can think and learn like humans. To do so, I focus on challenging issues in the current learning system both in the 'model' and 'data' perspective. Specifically, there are two principal directions I have explored. First, apart from the current model design paradigm, I attempted to incorporate the attention mechanism, a central component of the human vision system, into the model. Second, to reduce expensive and error-prone human supervision, I tried to exploit self-supervision or simulation and scale the training data up to a billion-scale.
My work explores following areas
Visual Perception (Categorization, Detection, Segmentation)
Visual Reasoning (Scene Graph, Summarization, Stroytelling)
Image and Video Processing (Synthesis, Translation)
Unsupervised / Self-supervised Learning
Simulated Learning and Domain Adaptation
but not limited to.
Research Experience
Adobe Research, San Jose, CA
KAIST, Daejeon, Korea
International Publications (Google Scholar)
(* indicates equal contribution)
2021
The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation [Paper]
2020
Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation [Paper]
Align-and-Attend Network for Globally and Locally Coherent Video Inpainting [Paper]
Two-Phase Pseudo Label Densification for Self-training based Domain Adaptation [Paper]
Global-and-Local Relative Position Embedding for Unsupervised Video Summarization [Paper]
Dahun Kim, Sanghyun Woo, Joon-Young Lee, In So KweonIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 (Oral)
A Simple and Light-weight Attention Module for Convolutional Neural Networks [Paper]
Recurrent Temporal Aggregaation Framework for Deep Video Inpainting [Paper]
Hide-and-Tell: Learning to Bridge Photo Streams for Visual Storytelling [Paper]
Propose-and-Attend Single Shot Detector [Paper]
2019
Preserving Semantic and Temporal Consistency for Unpaired Video-to-Video Translation [Paper]
Video Retargeting: Trade-off between Content Preservation and Spatio-temporal Consistency [Paper]
Dahun Kim*, Sanghyun Woo*, Joon-Young Lee, In So KweonIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Dahun Kim*, Sanghyun Woo*, Joon-Young Lee, In So KweonIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019The winner method of ECCV 2018 ChaLearnLAP Inpainting Challenge [factsheet]
Gated Bidirectional Feature Pyramid Network for Accurate One Shot Detection [Paper]
Discriminative Feature Learning for Unsupervised Video Summarization [Paper]
2018
LinkNet: Relational Embedding for Scene Graph [Paper]
Sanghyun Woo*, Jongchan Park*, Joon-Young Lee, In So KweonEuropean Conference on Computer Vision (ECCV), 2018
Jongchan Park*, Sanghyun Woo*, Joon-Young Lee, In So KweonBritish Machine Vision Conference (BMVC), 2018 (Oral)Received Gold Prize, 24th HumanTech Paper Award, Samsung Electronics Co., Ltd.
Sanghyun Woo, Soonmin Hwang, In So KweonWinter Conference on Computer Vision (WACV), 2018 (Oral)Received Silver Prize, Best Paper Award, 30th IPIU 2018Received Honorable Mention, 24th HumanTech Paper Award, Samsung Electronics Co., Ltd.
Academic Activities
Journal Reviewer
-Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
-International Journal of Computer Vision (IJCV)
-Transactions on Image Processing (TIP)
-Transactions on Circuits and Systems for Video Technology (TCSVT)
-Transactions on Cybernetics
-Machine Vision Applications (MVA)
-Pattern Recognition (PR)
-Neurocomputing
-IEEE Access
Conference Reviewer
-CVPR 2019, 2020, 2021
-ICCV 2019, 2021
-ECCV 2020
-BMVC 2020
-WACV 2020, 2021
-ACCV 2020
-NeurIPS 2020
-ICLR 2021
-AAAI 2020
Awards & Honors
Awards
-KAIST-Samsung Industry-University Cooperation Best Paper Award ($3,000), July 2020
-Honorable Mention, 25th HumanTech Paper Award, Samsung Electronics Co., Ltd. ($2,000), Feb 2019
-1st Place Award in ChaLearnLAP 2018 Inpainting Challenge Track 2 – video decaptioning (ECCV2018 Challenge), Sep 2018 [factsheet]
-Gold Prize, 24th HumanTech Paper Award, Samsung Electronics Co., Ltd. ($10,000), Feb 2018
-Honorable Mention, 24th HumanTech Paper Award, Samsung Electronics Co., Ltd. ($2,000), Feb 2018
-Silver Prize, Best Paper Award, 30th IPIU 2018, Feb 2018
Honors
-Microsoft Research Asia Ph.D. Fellowship 2020 Winner ($10,000), Nov 2020 [Certificate]
-AI summer school (PAISS 2018), July 2018