Zobrazeno 1 - 10
of 95
pro vyhledávání: '"Kandula, Praveen"'
Autor:
Kandula, Praveen, Rajagopalan, A. N.
Satellite images are typically subject to multiple distortions. Different factors affect the quality of satellite images, including changes in atmosphere, surface reflectance, sun illumination, viewing geometries etc., limiting its application to dow
Externí odkaz:
http://arxiv.org/abs/2306.02921
Autor:
Kandula, Praveen, Rajagopalan, A. N.
Several supervised networks exist that remove haze information from underwater images using paired datasets and pixel-wise loss functions. However, training these networks requires large amounts of paired data which is cumbersome, complex and time-co
Externí odkaz:
http://arxiv.org/abs/2306.02912
Supervised networks address the task of low-light enhancement using paired images. However, collecting a wide variety of low-light/clean paired images is tedious as the scene needs to remain static during imaging. In this paper, we propose an unsuper
Externí odkaz:
http://arxiv.org/abs/2306.02883
Autor:
Kandula, Praveen, N, Rajagopalan. A.
In the literature, coarse-to-fine or scale-recurrent approach i.e. progressively restoring a clean image from its low-resolution versions has been successfully employed for single image deblurring. However, a major disadvantage of existing methods is
Externí odkaz:
http://arxiv.org/abs/2112.06175
Autor:
Ignatov, Andrey, Timofte, Radu, Qian, Ming, Qiao, Congyu, Lin, Jiamin, Guo, Zhenyu, Li, Chenghua, Leng, Cong, Cheng, Jian, Peng, Juewen, Luo, Xianrui, Xian, Ke, Wu, Zijin, Cao, Zhiguo, Puthussery, Densen, C V, Jiji, S, Hrishikesh P, Kuriakose, Melvin, Dutta, Saikat, Das, Sourya Dipta, Shah, Nisarg A., Purohit, Kuldeep, Kandula, Praveen, Suin, Maitreya, Rajagopalan, A. N., B, Saagara M, L, Minnu A, R, Sanjana A, S, Praseeda, Wu, Ge, Chen, Xueqin, Wang, Tengyao, Zheng, Max, Wong, Hulk, Zou, Jay
This paper reviews the second AIM realistic bokeh effect rendering challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world bokeh simulation problem, where the goal was to learn a
Externí odkaz:
http://arxiv.org/abs/2011.04988
Autor:
Lugmayr, Andreas, Danelljan, Martin, Timofte, Radu, Fritsche, Manuel, Gu, Shuhang, Purohit, Kuldeep, Kandula, Praveen, Suin, Maitreya, Rajagopalan, A N, Joon, Nam Hyung, Won, Yu Seung, Kim, Guisik, Kwon, Dokyeong, Hsu, Chih-Chung, Lin, Chia-Hsiang, Huang, Yuanfei, Sun, Xiaopeng, Lu, Wen, Li, Jie, Gao, Xinbo, Bell-Kligler, Sefi
This paper reviews the AIM 2019 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting, where paired true high and low-resolution images are unavailable. For
Externí odkaz:
http://arxiv.org/abs/1911.07783
Autor:
Yuan, Shanxin, Timofte, Radu, Slabaugh, Gregory, Leonardis, Ales, Zheng, Bolun, Ye, Xin, Tian, Xiang, Chen, Yaowu, Cheng, Xi, Fu, Zhenyong, Yang, Jian, Hong, Ming, Lin, Wenying, Yang, Wenjin, Qu, Yanyun, Shin, Hong-Kyu, Kim, Joon-Yeon, Ko, Sung-Jea, Dong, Hang, Guo, Yu, Wang, Jie, Ding, Xuan, Han, Zongyan, Das, Sourya Dipta, Purohit, Kuldeep, Kandula, Praveen, Suin, Maitreya, Rajagopalan, A. N.
This paper reviews the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019. This paper describes the challenge, and focuses on the proposed solutions and their r
Externí odkaz:
http://arxiv.org/abs/1911.03461
Autor:
Ignatov, Andrey, Timofte, Radu, Van Vu, Thang, Luu, Tung Minh, Pham, Trung X, Van Nguyen, Cao, Kim, Yongwoo, Choi, Jae-Seok, Kim, Munchurl, Huang, Jie, Ran, Jiewen, Xing, Chen, Zhou, Xingguang, Zhu, Pengfei, Geng, Mingrui, Li, Yawei, Agustsson, Eirikur, Gu, Shuhang, Van Gool, Luc, de Stoutz, Etienne, Kobyshev, Nikolay, Nie, Kehui, Zhao, Yan, Li, Gen, Tong, Tong, Gao, Qinquan, Hanwen, Liu, Michelini, Pablo Navarrete, Dan, Zhu, Fengshuo, Hu, Hui, Zheng, Wang, Xiumei, Deng, Lirui, Meng, Rang, Qin, Jinghui, Shi, Yukai, Wen, Wushao, Lin, Liang, Feng, Ruicheng, Wu, Shixiang, Dong, Chao, Qiao, Yu, Vasu, Subeesh, Madam, Nimisha Thekke, Kandula, Praveen, Rajagopalan, A. N., Liu, Jie, Jung, Cheolkon
This paper reviews the first challenge on efficient perceptual image enhancement with the focus on deploying deep learning models on smartphones. The challenge consisted of two tracks. In the first one, participants were solving the classical image s
Externí odkaz:
http://arxiv.org/abs/1810.01641
Akademický článek
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Publikováno v:
In Medical Clinics of North America May 2016 100(3):487-503
