Standstill Parameter Identification of Vector-Controlled Induction Motor Using Frequency Characteristics of Rotor Bars. - Young-Su Kwon; Jeong-Hum Lee; Sang-Ho Moon; Byung-Ki Kwon; Chang-Ho Choi; Jul-Ki Seok (IAS, 2008)

DFlow: Learning to Synthesize Better Optical Flow Datasets via a Differentiable Pipeline. - Byung-Ki Kwon; Nam Hyeon-Woo; Ji-Yun Kim; Tae-Hyun Oh (ICLR, 2023)

The Devil in the Details: Simple and Effective Optical Flow Synthetic Data Generation. - Byung-Ki Kwon; Kim Sung-Bin; Tae-Hyun Oh (CoRR, 2023)

Learning-based Axial Motion Magnification. - Byung-Ki Kwon; Oh Hyun-Bin; Kim Jun-Seong; Tae-Hyun Oh (CoRR, 2023)

The Devil Is in the Details: Simple Remedies for Image-to-LiDAR Representation Learning. - Wonjun Jo; Byung-Ki Kwon; Kim Ji-Yeon; Hawook Jeong; Kyungdon Joo; Tae-Hyun Oh (ACCV (9), 2024)

Learning-based Axial Video Motion Magnification. - Byung-Ki Kwon; Oh Hyun-Bin; Kim Jun-Seong; Hyunwoo Ha; Tae-Hyun Oh (ECCV (54), 2024)

Revisiting Learning-based Video Motion Magnification for Real-time Processing. - Hyunwoo Ha; Oh Hyun-Bin; Kim Jun-Seong; Byung-Ki Kwon; Kim Sung-Bin; Linh-Tam Tran; Ji-Yun Kim; Sung-Ho Bae; Tae-Hyun Oh (CoRR, 2024)

Uni-DVPS: Unified Model for Depth-Aware Video Panoptic Segmentation. - Ji-Yeon Kim; Oh Hyun-Bin; Byung-Ki Kwon; Dahun Kim; Yongjin Kwon; Tae-Hyun Oh (IEEE Robotics Autom. Lett., 2024)

The devil in the details: simple and effective optical flow synthetic data generation. - Byung-Ki Kwon; Sung-Bin Kim; Tae-Hyun Oh (Vis. Comput., 2024)

Zero-shot Depth Completion via Test-time Alignment with Affine-invariant Depth Prior. - Hyoseok Lee; Kyeong Seon Kim; Byung-Ki Kwon; Tae-Hyun Oh (AAAI, 2025)

JointDiT: Enhancing RGB-Depth Joint Modeling with Diffusion Transformers. - Byung-Ki Kwon; Qi Dai; Hyoseok Lee; Chong Luo; Tae-Hyun Oh (CoRR, 2025)