Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Brian McWilliams"'
Autor:
Fabrice Rousselle, David Adler, Gerhard Rothlin, Mark Meyer, Brian McWilliams, Thijs Vogels, Jan Novák, Alex Harvill
Publikováno v:
ACM Transactions on Graphics. 37:1-15
We present a modular convolutional architecture for denoising rendered images. We expand on the capabilities of kernel-predicting networks by combining them with a number of task-specific modules, and optimizing the assembly using an asymmetric loss.
Autor:
Alex Harvill, Fabrice Rousselle, Tony DeRose, Steve Bako, Jan Novák, Brian McWilliams, Thijs Vogels, Pradeep Sen, Mark Meyer
Publikováno v:
ACM Transactions on Graphics. 36:1-14
Regression-based algorithms have shown to be good at denoising Monte Carlo (MC) renderings by leveraging its inexpensive by-products (e.g., feature buffers). However, when using higher-order models to handle complex cases, these techniques often over
Publikováno v:
EUSIPCO
In this paper we study deep learning-based music source separation, and explore using an alternative loss to the standard spectrogram pixel-level L2 loss for model training. Our main contribution is in demonstrating that adding a high-level feature l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::326a1dcfef6559a1a8840f5c3f4c575a
We propose to use deep neural networks for generating samples in Monte Carlo integration. Our work is based on non-linear independent components estimation (NICE), which we extend in numerous ways to improve performance and enable its application to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4cd1fd7077d81c07e73ee75777e6c25a
http://arxiv.org/abs/1808.03856
http://arxiv.org/abs/1808.03856
Autor:
Christopher Schroers, Alexander Sorkine-Hornung, Yifan Wang, Olga Sorkine-Hornung, Brian McWilliams, Federico Perazzi
Publikováno v:
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
CVPR Workshops
CVPR Workshops
Recent deep learning approaches to single image super-resolution have achieved impressive results in terms of traditional error measures and perceptual quality. However, in each case it remains challenging to achieve high quality results for large up
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::794a71797bb5313f57a35cf85734ce88
https://hdl.handle.net/20.500.11850/321437
https://hdl.handle.net/20.500.11850/321437
Autor:
Brian McWilliams, Simone Meyer, Alexander Sorkine-Hornung, Markus Gross, Christopher Schroers, Abdelaziz Djelouah
Publikováno v:
CVPR
Most approaches for video frame interpolation require accurate dense correspondences to synthesize an in-between frame. Therefore, they do not perform well in challenging scenarios with e.g. lighting changes or motion blur. Recent deep learning appro
Autor:
Radu Timofte, Shuhang Gu, Jiqing Wu, Luc Van Gool, Lei Zhang, Ming-Hsuan Yang, Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita, Shijia Hu, Yijie Bei, Zheng Hui, Xiao Jiang, Yanan Gu, Jie Liu, Yifan Wang, Federico Perazzi, Brian McWilliams, Alexander Sorkine-Hornung, Olga Sorkine-Hornung, Christopher Schroers, Jiahui Yu, Yuchen Fan, Jianchao Yang, Ning Xu, Zhaowen Wang, Xinchao Wang, Thomas S. Huang, Xintao Wang, Ke Yu, Tak-Wai Hui, Chao Dong, Liang Lin, Chen Change Loy, Dongwon Park, Kwanyoung Kim, Se Young Chun, Kai Zhang, Pengjv Liu, Wangmeng Zuo, Shi Guo, Jiye Liu, Jinchang Xu, Yijiao Liu, Fengye Xiong, Yuan Dong, Hongliang Bai, Alexandru Damian, Nikhil Ravi, Sachit Menon, Cynthia Rudin, Junghoon Seo, Taegyun Jeon, Jamyoung Koo, Seunghyun Jeon, Soo Ye Kim, Jae-Seok Choi, Sehwan Ki, Soomin Seo, Hyeonjun Sim, Saehun Kim, Munchurl Kim, Rong Chen, Kun Zeng, Jinkang Guo, Yanyun Qu, Cuihua Li, Namhyuk Ahn, Byungkon Kang, Kyung-Ah Sohn, Yuan Yuan, Jiawei Zhang, Jiahao Pang, Xiangyu Xu, Yan Zhao, Wei Deng, Sibt Ul Hussain, Muneeb Aadil, Rafia Rahim, Xiaowang Cai, Fang Huang, Yueshu Xu, Pablo Navarrete Michelini, Dan Zhu, Hanwen Liu, Jun-Hyuk Kim, Jong-Seok Lee, Yiwen Huang, Ming Qiu, Liting Jing, Jiehang Zeng, Ying Wang, Manoj Sharma, Rudrabha Mukhopadhyay, Avinash Upadhyay, Sriharsha Koundinya, Ankit Shukla, Santanu Chaudhury, Zhe Zhang, Yu Hen Hu, Lingzhi Fu
Publikováno v:
CVPR Workshops
This paper reviews the 2nd NTIRE challenge on single image super-resolution (restoration of rich details in a low resolution image) with focus on proposed solutions and results. The challenge had 4 tracks. Track 1 employed the standard bicubic downsc
We present a technique for efficiently synthesizing images of atmospheric clouds using a combination of Monte Carlo integration and neural networks. The intricacies of Lorenz-Mie scattering and the high albedo of cloud-forming aerosols make rendering
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c42298cc432b5ab4cfc28de5bdfa6372
http://arxiv.org/abs/1709.05418
http://arxiv.org/abs/1709.05418
Autor:
Federico Perazzi, Markus Gross, Brian McWilliams, Alexander Sorkine-Hornung, L. Van Gool, Jordi Pont-Tuset
Publikováno v:
CVPR
Over the years, datasets and benchmarks have proven their fundamental importance in computer vision research, enabling targeted progress and objective comparisons in many fields. At the same time, legacy datasets may impend the evolution of a field d
Autor:
Giovanni Montana, Brian McWilliams
Publikováno v:
Statistical Analysis and Data Mining: The ASA Data Science Journal. 5:304-321
Many modern data mining applications are concerned with the analysis of datasets in which the observations are described by paired high-dimensional vectorial representations or ‘views’. Some typical examples can be found in web mining and genomic