Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report

no code implementations • 17 May 2021 • Andrey Ignatov, Kim Byeoung-su, Radu Timofte, Angeline Pouget, Fenglong Song, Cheng Li, Shuai Xiao, Zhongqian Fu, Matteo Maggioni, Yibin Huang, Shen Cheng, Xin Lu, Yifeng Zhou, Liangyu Chen, Donghao Liu, Xiangyu Zhang, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Minsu Kwon, Myungje Lee, Jaeyoon Yoo, Changbeom Kang, Shinjo Wang, Bin Huang, Tianbao Zhou, Shuai Liu, Lei Lei, Chaoyu Feng, Liguang Huang, Zhikun Lei, Feifei Chen

A detailed description of all models developed in the challenge is provided in this paper.

Image Denoising

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

1 code implementation • 21 Apr 2021 • Ren Yang, Radu Timofte, Jing Liu, Yi Xu, Xinjian Zhang, Minyi Zhao, Shuigeng Zhou, Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy, Xin Li, Fanglong Liu, He Zheng, Lielin Jiang, Qi Zhang, Dongliang He, Fu Li, Qingqing Dang, Yibin Huang, Matteo Maggioni, Zhongqian Fu, Shuai Xiao, Cheng Li, Thomas Tanay, Fenglong Song, Wentao Chao, Qiang Guo, Yan Liu, Jiang Li, Xiaochao Qu, Dewang Hou, Jiayu Yang, Lyn Jiang, Di You, Zhenyu Zhang, Chong Mou, Iaroslav Koshelev, Pavel Ostyakov, Andrey Somov, Jia Hao, Xueyi Zou, Shijie Zhao, Xiaopeng Sun, Yiting Liao, Yuanzhi Zhang, Qing Wang, Gen Zhan, Mengxi Guo, Junlin Li, Ming Lu, Zhan Ma, Pablo Navarrete Michelini, Hai Wang, Yiyun Chen, Jingyu Guo, Liliang Zhang, Wenming Yang, Sijung Kim, Syehoon Oh, Yucong Wang, Minjie Cai, Wei Hao, Kangdi Shi, Liangyan Li, Jun Chen, Wei Gao, Wang Liu, XiaoYu Zhang, Linjie Zhou, Sixin Lin, Ru Wang

This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results.

Efficient Multi-Stage Video Denoising with Recurrent Spatio-Temporal Fusion

1 code implementation • CVPR 2021 • Matteo Maggioni, Yibin Huang, Cheng Li, Shuai Xiao, Zhongqian Fu, Fenglong Song

Then, a denoising stage removes the noise in the fused frame.

Denoising Video Denoising

Learning Temporal Point Processes via Reinforcement Learning

no code implementations • NeurIPS 2018 • Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song

Social goods, such as healthcare, smart city, and information networks, often produce ordered event data in continuous time.

Point Processes

Modeling The Intensity Function Of Point Process Via Recurrent Neural Networks

2 code implementations • 24 May 2017 • Shuai Xiao, Junchi Yan, Stephen M. Chu, Xiaokang Yang, Hongyuan Zha

In this paper, we model the background by a Recurrent Neural Network (RNN) with its units aligned with time series indexes while the history effect is modeled by another RNN whose units are aligned with asynchronous events to capture the long-range dynamics.

Point Processes Time Series

Wasserstein Learning of Deep Generative Point Process Models

1 code implementation • NeurIPS 2017 • Shuai Xiao, Mehrdad Farajtabar, Xiaojing Ye, Junchi Yan, Le Song, Hongyuan Zha

Point processes are becoming very popular in modeling asynchronous sequential data due to their sound mathematical foundation and strength in modeling a variety of real-world phenomena.

Point Processes

Joint Modeling of Event Sequence and Time Series with Attentional Twin Recurrent Neural Networks

no code implementations • 24 Mar 2017 • Shuai Xiao, Junchi Yan, Mehrdad Farajtabar, Le Song, Xiaokang Yang, Hongyuan Zha

A variety of real-world processes (over networks) produce sequences of data whose complex temporal dynamics need to be studied.

Point Processes Time Series