no code implementations • 25 Apr 2023 • Mark Wronkiewicz, Jake Lee, Lukas Mandrake, Jack Lightholder, Gary Doran, Steffen Mauceri, Taewoo Kim, Nathan Oborny, Thomas Schibler, Jay Nadeau, James K. Wallace, Eshaan Moorjani, Chris Lindensmith
Such an instrument suite could generate 10, 000x more raw data than is possible to transmit from distant ocean worlds like Enceladus or Europa.
no code implementations • 28 Mar 2023 • Jaeseong Lee, Taewoo Kim, Sunghyun Park, Younggun Lee, Jaegul Choo
However, we observed that previous approaches still suffer from source attribute leakage, where the source image's attributes interfere with the target image's.
1 code implementation • CVPR 2023 • Taewoo Kim, Yujeong Chae, Hyun-Kurl Jang, Kuk-Jin Yoon
Video Frame Interpolation (VFI) aims to generate intermediate video frames between consecutive input frames.
no code implementations • ICCV 2023 • Hoonhee Cho, Yuhwan Jeong, Taewoo Kim, Kuk-Jin Yoon
Motion deblurring from a blurred image is a challenging computer vision problem because frame-based cameras lose information during the blurring process.
no code implementations • 18 Nov 2022 • Ho Suk, Taewoo Kim, Hyungbin Park, Pamul Yadav, Junyong Lee, Shiho Kim
Despite the rapid improvement of autonomous driving technology in recent years, automotive manufacturers must resolve liability issues to commercialize autonomous passenger car of SAE J3016 Level 3 or higher.
1 code implementation • 15 Sep 2022 • Jinhee Kim, Taesung Kim, Taewoo Kim, Jaegul Choo, Dong-Wook Kim, Byungduk Ahn, In-Seok Song, Yoon-Ji Kim
To fully automate this procedure, deep-learning-based methods have been widely proposed and have achieved high performance in detecting keypoints in medical images.
1 code implementation • 16 Aug 2022 • Taewoo Kim, Chaeyeon Chung, Yoonseo Kim, Sunghyun Park, Kangyeol Kim, Jaegul Choo
Editing hairstyle is unique and challenging due to the complexity and delicacy of hairstyle.
no code implementations • 17 Jun 2022 • Chaeyeon Chung, Taewoo Kim, Hyelin Nam, Seunghwan Choi, Gyojung Gu, Sunghyun Park, Jaegul Choo
Hairstyle transfer is the task of modifying a source hairstyle to a target one.
no code implementations • 13 Dec 2021 • Taewoo Kim, Jeongmin Lee, Lin Wang, Kuk-Jin Yoon
To this end, we first derive a new formulation for event-guided motion deblurring by considering the exposure and readout time in the video frame acquisition process.
no code implementations • 29 Sep 2021 • Minsu Jeon, Kyungno Joo, Changha Lee, Taewoo Kim, SeongHwan Kim, Chan-Hyun Youn
In a restricted computing environment like satellite on-board systems, running DL models has limitation on high-speed processing due to the problems such as restriction of available power to consume compared to the relatively high computational complexity.
no code implementations • 11 Feb 2021 • Taewoo Kim, Chaeyeon Chung, Sunghyun Park, Gyojung Gu, Keonmin Nam, Wonzo Choe, Jaesung Lee, Jaegul Choo
In response, we introduce a novel large-scale Korean hairstyle dataset, K-hairstyle, containing 500, 000 high-resolution images.
no code implementations • 12 Jan 2020 • Il Bae, Jaeyoung Moon, Junekyo Jhung, Ho Suk, Taewoo Kim, Hyungbin Park, Jaekwang Cha, Jinhyuk Kim, Dohyun Kim, Shiho Kim
Moreover, we propose a vehicle controller based on control parameters enabling integrated lateral and longitudinal control via preference-aware maneuvering of autonomous vehicles.
no code implementations • 26 Sep 2019 • Woo-han Yun, Taewoo Kim, Jaeyeon Lee, Jaehong Kim, Junmo Kim
Then, we show that the original cut-and-paste approach suffers from a new domain gap problem, an unbalanced domain gaps, because it has two separate source domains for foreground and background, unlike the conventional domain shift problem.
no code implementations • 25 Sep 2019 • Heejae Kim, Taewoo Kim, Chan-Hyun Youn
Federated learning, where a global model is trained by iterative parameter averaging of locally-computed updates, is a promising approach for distributed training of deep networks; it provides high communication-efficiency and privacy-preservability, which allows to fit well into decentralized data environments, e. g., mobile-cloud ecosystems.
3 code implementations • 25 Sep 2019 • Taewoo Kim, Joo-Haeng Lee
The motion retargeting learning is performed using refined data in a latent space by the cyclic and filtering paths of our method.