Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Chun, Se Young"'
Autor:
Hong, Seongmin, Chun, Se Young
Normalizing flows have been successfully modeling a complex probability distribution as an invertible transformation of a simple base distribution. However, there are often applications that require more than invertibility. For instance, the computat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5fca4755e758380a0447b87c000a170e
http://arxiv.org/abs/2304.04555
http://arxiv.org/abs/2304.04555
The increasing demand for high-quality 3D content creation has motivated the development of automated methods for creating 3D object models from a single image and/or from a text prompt. However, the reconstructed 3D objects using state-of-the-art im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::425f6fb2ce4802e933ed45dab0cab193
http://arxiv.org/abs/2304.02827
http://arxiv.org/abs/2304.02827
Recently, significant advancements have been made in 3D generative models, however training these models across diverse domains is challenging and requires an huge amount of training data and knowledge of pose distribution. Text-guided domain adaptat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f0952836456bf3ff72fe19262076cf40
Autor:
Lee, Haechang, Park, Dongwon, Jeong, Wongi, Kim, Kijeong, Je, Hyunwoo, Ryu, Dongil, Chun, Se Young
As the physical size of recent CMOS image sensors (CIS) gets smaller, the latest mobile cameras are adopting unique non-Bayer color filter array (CFA) patterns (e.g., Quad, Nona, QxQ), which consist of homogeneous color units with adjacent pixels. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::52d14429cbfccbf5e977fb300d2f10f6
Conditional normalizing flows can generate diverse image samples for solving inverse problems. Most normalizing flows for inverse problems in imaging employ the conditional affine coupling layer that can generate diverse images quickly. However, unin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d07d2690f5c85371042b9cbea6045a61
http://arxiv.org/abs/2212.04319
http://arxiv.org/abs/2212.04319
Autor:
Kim, Gwanghyun, Chun, Se Young
Recent 3D generative models have achieved remarkable performance in synthesizing high resolution photorealistic images with view consistency and detailed 3D shapes, but training them for diverse domains is challenging since it requires massive traini
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98f86a26af1d35b08021002536846764
http://arxiv.org/abs/2211.16374
http://arxiv.org/abs/2211.16374
Autor:
Ignatov, Andrey, Malivenko, Grigory, Timofte, Radu, Treszczotko, Lukasz, Chang, Xin, Ksiazek, Piotr, Lopuszynski, Michal, Pioro, Maciej, Rudnicki, Rafal, Smyl, Maciej, Ma, Yujie, Li, Zhenyu, Chen, Zehui, Xu, Jialei, Liu, Xianming, Jiang, Junjun, Shi, XueChao, Xu, Difan, Li, Yanan, Wang, Xiaotao, Lei, Lei, Zhang, Ziyu, Wang, Yicheng, Huang, Zilong, Luo, Guozhong, Yu, Gang, Fu, Bin, Li, Jiaqi, Wang, Yiran, Huang, Zihao, Cao, Zhiguo, Conde, Marcos V., Sapozhnikov, Denis, Lee, Byeong Hyun, Park, Dongwon, Hong, Seongmin, Lee, Joonhee, Lee, Seunggyu, Chun, Se Young
Various depth estimation models are now widely used on many mobile and IoT devices for image segmentation, bokeh effect rendering, object tracking and many other mobile tasks. Thus, it is very crucial to have efficient and accurate depth estimation m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4dc8ef5420f08b1eb5c315a153b38ae0
http://arxiv.org/abs/2211.04470
http://arxiv.org/abs/2211.04470
Autor:
Ignatov, Andrey, Timofte, Radu, Denna, Maurizio, Younes, Abdel, Gankhuyag, Ganzorig, Huh, Jingang, Kim, Myeong Kyun, Yoon, Kihwan, Moon, Hyeon-Cheol, Lee, Seungho, Choe, Yoonsik, Jeong, Jinwoo, Kim, Sungjei, Smyl, Maciej, Latkowski, Tomasz, Kubik, Pawel, Sokolski, Michal, Ma, Yujie, Chao, Jiahao, Zhou, Zhou, Gao, Hongfan, Yang, Zhengfeng, Zeng, Zhenbing, Zhuge, Zhengyang, Li, Chenghua, Zhu, Dan, Sun, Mengdi, Duan, Ran, Gao, Yan, Kong, Lingshun, Sun, Long, Li, Xiang, Zhang, Xingdong, Zhang, Jiawei, Wu, Yaqi, Pan, Jinshan, Yu, Gaocheng, Zhang, Jin, Zhang, Feng, Ma, Zhe, Wang, Hongbin, Cho, Hojin, Kim, Steve, Li, Huaen, Ma, Yanbo, Luo, Ziwei, Li, Youwei, Yu, Lei, Wen, Zhihong, Wu, Qi, Fan, Haoqiang, Liu, Shuaicheng, Zhang, Lize, Zong, Zhikai, Kwon, Jeremy, Zhang, Junxi, Li, Mengyuan, Fu, Nianxiang, Ding, Guanchen, Zhu, Han, Chen, Zhenzhong, Li, Gen, Zhang, Yuanfan, Sun, Lei, Zhang, Dafeng, Yang, Neo, Liu, Fitz, Zhao, Jerry, Ayazoglu, Mustafa, Bilecen, Bahri Batuhan, Hirose, Shota, Arunruangsirilert, Kasidis, Ao, Luo, Leung, Ho Chun, Wei, Andrew, Liu, Jie, Liu, Qiang, Yu, Dahai, Li, Ao, Luo, Lei, Zhu, Ce, Hong, Seongmin, Park, Dongwon, Lee, Joonhee, Lee, Byeong Hyun, Lee, Seunggyu, Chun, Se Young, He, Ruiyuan, Jiang, Xuhao, Ruan, Haihang, Zhang, Xinjian, Liu, Jing, Gendy, Garas, Sabor, Nabil, Hou, Jingchao, He, Guanghui
Image super-resolution is a common task on mobile and IoT devices, where one often needs to upscale and enhance low-resolution images and video frames. While numerous solutions have been proposed for this problem in the past, they are usually not com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20fc9c108313591d2347ccdb20404264
http://arxiv.org/abs/2211.05910
http://arxiv.org/abs/2211.05910
Regression that predicts continuous quantity is a central part of applications using computational imaging and computer vision technologies. Yet, studying and understanding self-supervised learning for regression tasks - except for a particular regre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21a7d738d5192b3c6cfe2ee6642218f1
http://arxiv.org/abs/2205.04821
http://arxiv.org/abs/2205.04821
Publikováno v:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
IEEE/CVF Winter Conference on Applications of Computer Vision
IEEE/CVF Winter Conference on Applications of Computer Vision
Ill-posed inverse problems appear in many image processing applications, such as deblurring and super-resolution. In recent years, solutions that are based on deep Convolutional Neural Networks (CNNs) have shown great promise. Yet, most of these tech