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.
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.
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.
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.
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.
Ranked #3 on Video Denoising on CRVD
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.
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.
1 code implementation • 30 May 2022 • Jiachen Yang, Zhuo Zhang, Yicheng Gong, Shukun Ma, Xiaolan Guo, Yue Yang, Shuai Xiao, Jiabao Wen, Yang Li, Xinbo Gao, Wen Lu, Qinggang Meng
Data has now become a shortcoming of deep learning.
no code implementations • 20 Jun 2022 • Wei Li, Shuai Xiao, Tianhong Dai, Shanxin Yuan, Tao Wang, Cheng Li, Fenglong Song
To further leverage these two paradigms, we propose a selective and joint HDR and denoising (SJ-HD$^2$R) imaging framework, utilizing scenario-specific priors to conduct the path selection with an accuracy of more than 93. 3$\%$.
no code implementations • 2 Mar 2023 • Shuai Xiao, Le Guo, Zaifan Jiang, Lei Lv, Yuanbo Chen, Jun Zhu, Shuang Yang
Furthermore, we show that the dual problem can be solved by policy learning, with the optimal dual variable being found efficiently via bisection search (i. e., by taking advantage of the monotonicity).
no code implementations • 3 Mar 2023 • Shuai Xiao, Zaifan Jiang, Shuang Yang
Finding optimal configurations in a geometric space is a key challenge in many technological disciplines.
no code implementations • 6 May 2023 • Zida Cheng, Chen Ju, Xu Chen, Zhonghua Zhai, Shuai Xiao, Xiaoyi Zeng, Weilin Huang
We formally define a novel valuable information retrieval task: image-to-multi-modal-retrieval (IMMR), where the query is an image and the doc is an entity with both image and textual description.
no code implementations • 6 May 2023 • Xu Chen, Zida Cheng, Shuai Xiao, Xiaoyi Zeng, Weilin Huang
The translation network is able to compute features from two domains with heterogeneous inputs separately by designing two independent branches, and then learn meaningful cross-domain knowledge using a designed cross-supervised feature translator.
no code implementations • 16 Jun 2023 • Shuai Xiao, Chen Pan, Min Wang, Xinxin Zhu, Siqiao Xue, Jing Wang, Yunhua Hu, James Zhang, Jinghua Feng
To this end, we formulate the problem as a partially observable Markov decision problem (POMDP) and employ an environment correction algorithm based on the characteristics of the business.
1 code implementation • 19 Sep 2023 • Shiwen Zhang, Shuai Xiao, Weilin Huang
Text-guided image editing on real or synthetic images, given only the original image itself and the target text prompt as inputs, is a very general and challenging task.
no code implementations • 30 Nov 2023 • Xu Chen, Zida Cheng, Jiangchao Yao, Chen Ju, Weilin Huang, Jinsong Lan, Xiaoyi Zeng, Shuai Xiao
Later the augmentation network employs the explicit cross-domain knowledge as augmented information to boost the target domain CTR prediction.
no code implementations • 12 Dec 2023 • Chen Ju, Haicheng Wang, Zeqian Li, Xu Chen, Zhonghua Zhai, Weilin Huang, Shuai Xiao
Vision-Language Large Models (VLMs) have become primary backbone of AI, due to the impressive performance.
no code implementations • 19 Mar 2024 • Mengting Chen, Xi Chen, Zhonghua Zhai, Chen Ju, Xuewen Hong, Jinsong Lan, Shuai Xiao
This paper introduces a novel framework for virtual try-on, termed Wear-Any-Way.
no code implementations • 22 Mar 2024 • Zhonghua Zhai, Chen Ju, Jinsong Lan, Shuai Xiao
In this work, we propose Cell Variational Information Bottleneck Network (cellVIB), a convolutional neural network using information bottleneck mechanism, which can be combined with the latest feedforward network architecture in an end-to-end training method.