3 code implementations • 19 Jan 2022 • Doyeon Kim, Woonghyun Ka, Pyungwhan Ahn, Donggyu Joo, Sehwan Chun, Junmo Kim
Depth estimation from a single image is an important task that can be applied to various fields in computer vision, and has grown rapidly with the development of convolutional neural networks.
Ranked #26 on Monocular Depth Estimation on KITTI Eigen split
no code implementations • 4 Sep 2020 • Do-Yeon Kim, Donggyu Joo, Junmo Kim
Advances in technology have led to the development of methods that can create desired visual multimedia.
no code implementations • CVPR 2020 • Janghyeon Lee, Hyeong Gwon Hong, Donggyu Joo, Junmo Kim
We propose a quadratic penalty method for continual learning of neural networks that contain batch normalization (BN) layers.
1 code implementation • 17 Feb 2020 • Janghyeon Lee, Donggyu Joo, Hyeong Gwon Hong, Junmo Kim
We propose a novel continual learning method called Residual Continual Learning (ResCL).
no code implementations • CVPR 2018 • Donggyu Joo, Do-Yeon Kim, Junmo Kim
Generating a novel image by manipulating two input images is an interesting research problem in the study of generative adversarial networks (GANs).
1 code implementation • CVPR 2017 • Junho Yim, Donggyu Joo, Jihoon Bae, Junmo Kim
We introduce a novel technique for knowledge transfer, where knowledge from a pretrained deep neural network (DNN) is distilled and transferred to another DNN.