no code implementations • ECCV 2020 • Yunjae Jung, Donghyeon Cho, Sanghyun Woo, In So Kweon
In order to summarize a content video properly, it is important to grasp the sequential structure of video as well as the long-term dependency between frames.
no code implementations • CVPR 2024 • Donggeun Yoon, Donghyeon Cho
Multiplane image (MPI) is desirable for social media because of its generality but it is complex and computationally expensive making object removal challenging.
1 code implementation • 5 Dec 2023 • Donggeun Yoon, Minseok Seo, Doyi Kim, Yeji Choi, Donghyeon Cho
We also introduce and evaluate the Pacific Northwest Windstorm (PNW)-Typhoon weather satellite dataset to verify the effectiveness of DGDM in high-resolution regional forecasting.
1 code implementation • 13 Apr 2023 • Seung Hyun Lee, Sieun Kim, Innfarn Yoo, Feng Yang, Donghyeon Cho, Youngseo Kim, Huiwen Chang, Jinkyu Kim, Sangpil Kim
We propose a method for adding sound-guided visual effects to specific regions of videos with a zero-shot setting.
no code implementations • CVPR 2023 • Dae-Young Song, HeeKyung Lee, Jeongil Seo, Donghyeon Cho
Beyond the SMPL, which provides skinned parametric human 3D information, in this paper, we propose a new IF-based method, DIFu, that utilizes a projected depth prior containing textured and non-parametric human 3D information.
1 code implementation • 14 Nov 2022 • Byungho Jo, Donghyeon Cho, In Kyu Park, Sungeun Hong
Existing face restoration models have relied on general assessment metrics that do not consider the characteristics of facial regions.
1 code implementation • 14 Oct 2022 • Donggeun Yoon, Jinsun Park, Donghyeon Cho
Therefore, there has been a demand for a lightweight alpha matting model due to the limited computational resources of commercial portable devices.
no code implementations • 13 Sep 2022 • Dae-Young Song, Geonsoo Lee, HeeKyung Lee, Gi-Mun Um, Donghyeon Cho
Recently, there has been growing attention on an end-to-end deep learning-based stitching model.
3 code implementations • 3 Jul 2020 • Youngeun Kim, Donghyeon Cho, Kyeongtak Han, Priyadarshini Panda, Sungeun Hong
Our key idea is to leverage a pre-trained model from the source domain and progressively update the target model in a self-learning manner.
no code implementations • CVPR 2021 • Seunghwan Lee, Donghyeon Cho, Jiwon Kim, Tae Hyun Kim
We analyze the restoration performance of the fine-tuned video denoising networks with the proposed self-supervision-based learning algorithm, and demonstrate that the FCN can utilize recurring patches without requiring accurate registration among adjacent frames.
no code implementations • 9 Mar 2020 • Seunghwan Lee, Dongkyu Lee, Donghyeon Cho, Jiwon Kim, Tae Hyun Kim
However, these methods have limitations in using internal information available in a given test image.
1 code implementation • ECCV 2020 • Seobin Park, Jinsu Yoo, Donghyeon Cho, Jiwon Kim, Tae Hyun Kim
In the training stage, we train the network via meta-learning; thus, the network can quickly adapt to any input image at test time.
no code implementations • 9 Jan 2020 • Seunghwan Lee, Donghyeon Cho, Jiwon Kim, Tae Hyun Kim
Under certain statistical assumptions of noise, recent self-supervised approaches for denoising have been introduced to learn network parameters without true clean images, and these methods can restore an image by exploiting information available from the given input (i. e., internal statistics) at test time.
1 code implementation • International Conference on Computer Vision Workshops 2019 • Dawei Du, Pengfei Zhu, Longyin Wen, Xiao Bian, Haibin Lin, QinGhua Hu, Tao Peng, Jiayu Zheng, Xinyao Wang, Yue Zhang, Liefeng Bo, Hailin Shi, Rui Zhu, Aashish Kumar, Aijin Li, Almaz Zinollayev, Anuar Askergaliyev, Arne Schumann, Binjie Mao, Byeongwon Lee, Chang Liu, Changrui Chen, Chunhong Pan, Chunlei Huo, Da Yu, Dechun Cong, Dening Zeng, Dheeraj Reddy Pailla, Di Li, Dong Wang, Donghyeon Cho, Dongyu Zhang, Furui Bai, George Jose, Guangyu Gao, Guizhong Liu, Haitao Xiong, Hao Qi, Haoran Wang, Heqian Qiu, Hongliang Li, Huchuan Lu, Ildoo Kim, Jaekyum Kim, Jane Shen, Jihoon Lee, Jing Ge, Jingjing Xu, Jingkai Zhou, Jonas Meier, Jun Won Choi, Junhao Hu, Junyi Zhang, Junying Huang, Kaiqi Huang, Keyang Wang, Lars Sommer, Lei Jin, Lei Zhang
Results of 33 object detection algorithms are presented.
no code implementations • 21 Aug 2019 • Kwanyong Park, Sanghyun Woo, Dahun Kim, Donghyeon Cho, In So Kweon
In this paper, we investigate the problem of unpaired video-to-video translation.
no code implementations • 18 Jun 2019 • Donghyeon Cho, Sungeun Hong, Sungil Kang, Jiwon Kim
After M-th frame, we select K IDs based on video saliency and frequency of appearance; then only these key IDs are tracked through the remaining frames.
1 code implementation • 24 Nov 2018 • Yunjae Jung, Donghyeon Cho, Dahun Kim, Sanghyun Woo, In So Kweon
The proposed variance loss allows a network to predict output scores for each frame with high discrepancy which enables effective feature learning and significantly improves model performance.
Ranked #3 on Unsupervised Video Summarization on SumMe
Supervised Video Summarization Unsupervised Video Summarization
no code implementations • 24 Nov 2018 • Dahun Kim, Donghyeon Cho, In So Kweon
Self-supervised tasks such as colorization, inpainting and zigsaw puzzle have been utilized for visual representation learning for still images, when the number of labeled images is limited or absent at all.
Ranked #42 on Self-Supervised Action Recognition on HMDB51
3 code implementations • NeurIPS 2018 • Sanghyun Woo, Dahun Kim, Donghyeon Cho, In So Kweon
In this paper, we present a method that improves scene graph generation by explicitly modeling inter-dependency among the entire object instances.
no code implementations • ECCV 2018 • Jinseok Park, Donghyeon Cho, Wonhyuk Ahn, Heung-Kyu Lee
Double JPEG detection is essential for detecting various image manipulations.
no code implementations • 6 Feb 2018 • Dahun Kim, Donghyeon Cho, Donggeun Yoo, In So Kweon
The recovery of the aforementioned damage pushes the network to obtain robust and general-purpose representations.
2 code implementations • ICCV 2017 • Donghyeon Cho, Jinsun Park, Tae-Hyun Oh, Yu-Wing Tai, In So Kweon
Our method implicitly learns an attention map, which leads to a content-aware shift map for image retargeting.
no code implementations • ICCV 2017 • Dahun Kim, Donghyeon Cho, Donggeun Yoo, In So Kweon
Weakly supervised semantic segmentation and localiza- tion have a problem of focusing only on the most important parts of an image since they use only image-level annota- tions.
1 code implementation • CVPR 2017 • Jinsun Park, Yu-Wing Tai, Donghyeon Cho, In So Kweon
In this paper, we introduce robust and synergetic hand-crafted features and a simple but efficient deep feature from a convolutional neural network (CNN) architecture for defocus estimation.
Ranked #2 on Defocus Estimation on CUHK - Blur Detection Dataset