1 code implementation • CVPR 2024 • Xinjie Zhang, Ren Yang, Dailan He, Xingtong Ge, Tongda Xu, Yan Wang, Hongwei Qin, Jun Zhang
Implicit neural representations (INRs) have emerged as a promising approach for video storage and processing, showing remarkable versatility across various video tasks.
no code implementations • 3 Feb 2023 • Ziyi Chen, Ren Yang, Sunyang Fu, Nansu Zong, Hongfang Liu, Ming Huang
In this work, we propose a hybrid deep learning model which combines a pretrained sentence BERT (SBERT) and convolutional neural network (CNN) to detect individuals with depression with their Reddit posts.
1 code implementation • 13 Nov 2022 • Ren Yang, Radu Timofte, Luc van Gool
In this paper, we propose an Advanced Learned Video Compression (ALVC) approach with the in-loop frame prediction module, which is able to effectively predict the target frame from the previously compressed frames, without consuming any bit-rate.
3 code implementations • 23 Aug 2022 • Ren Yang, Radu Timofte, Qi Zhang, Lin Zhang, Fanglong Liu, Dongliang He, Fu Li, He Zheng, Weihang Yuan, Pavel Ostyakov, Dmitry Vyal, Magauiya Zhussip, Xueyi Zou, Youliang Yan, Lei LI, Jingzhu Tang, Ming Chen, Shijie Zhao, Yu Zhu, Xiaoran Qin, Chenghua Li, Cong Leng, Jian Cheng, Claudio Rota, Marco Buzzelli, Simone Bianco, Raimondo Schettini, Dafeng Zhang, Feiyu Huang, Shizhuo Liu, Xiaobing Wang, Zhezhu Jin, Bingchen Li, Xin Li, Mingxi Li, Ding Liu, Wenbin Zou, Peijie Dong, Tian Ye, Yunchen Zhang, Ming Tan, Xin Niu, Mustafa Ayazoglu, Marcos Conde, Ui-Jin Choi, Zhuang Jia, Tianyu Xu, Yijian Zhang, Mao Ye, Dengyan Luo, Xiaofeng Pan, Liuhan Peng
The homepage of this challenge is at https://github. com/RenYang-home/AIM22_CompressSR.
2 code implementations • 20 Apr 2022 • Ren Yang, Radu Timofte, Meisong Zheng, Qunliang Xing, Minglang Qiao, Mai Xu, Lai Jiang, Huaida Liu, Ying Chen, Youcheng Ben, Xiao Zhou, Chen Fu, Pei Cheng, Gang Yu, Junyi Li, Renlong Wu, Zhilu Zhang, Wei Shang, Zhengyao Lv, Yunjin Chen, Mingcai Zhou, Dongwei Ren, Kai Zhang, WangMeng Zuo, Pavel Ostyakov, Vyal Dmitry, Shakarim Soltanayev, Chervontsev Sergey, Zhussip Magauiya, Xueyi Zou, Youliang Yan, Pablo Navarrete Michelini, Yunhua Lu, Diankai Zhang, Shaoli Liu, Si Gao, Biao Wu, Chengjian Zheng, Xiaofeng Zhang, Kaidi Lu, Ning Wang, Thuong Nguyen Canh, Thong Bach, Qing Wang, Xiaopeng Sun, Haoyu Ma, Shijie Zhao, Junlin Li, Liangbin Xie, Shuwei Shi, Yujiu Yang, Xintao Wang, Jinjin Gu, Chao Dong, Xiaodi Shi, Chunmei Nian, Dong Jiang, Jucai Lin, Zhihuai Xie, Mao Ye, Dengyan Luo, Liuhan Peng, Shengjie Chen, Qian Wang, Xin Liu, Boyang Liang, Hang Dong, Yuhao Huang, Kai Chen, Xingbei Guo, Yujing Sun, Huilei Wu, Pengxu Wei, Yulin Huang, Junying Chen, Ik Hyun Lee, Sunder Ali Khowaja, Jiseok Yoon
This challenge includes three tracks.
no code implementations • 8 Dec 2021 • Yannick Strümpler, Janis Postels, Ren Yang, Luc van Gool, Federico Tombari
Recently Implicit Neural Representations (INRs) gained attention as a novel and effective representation for various data types.
3 code implementations • 7 Sep 2021 • Ren Yang, Radu Timofte, Luc van Gool
This paper proposes a Perceptual Learned Video Compression (PLVC) approach with recurrent conditional GAN.
1 code implementation • 28 Jun 2021 • Jiang Hai, Zhu Xuan, Songchen Han, Ren Yang, Yutong Hao, Fengzhu Zou, Fang Lin
Solving a series of degradation of low-light images can effectively improve the visual quality of images and the performance of high-level visual tasks.
1 code implementation • CVPR 2021 • Xin Deng, Wenzhe Yang, Ren Yang, Mai Xu, Enpeng Liu, Qianhan Feng, Radu Timofte
To fully explore the mutual information across two stereo images, we use a deep regression model to estimate the homography matrix, i. e., H matrix.
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.
2 code implementations • 21 Apr 2021 • Ren Yang, Radu Timofte
In our study, we analyze the proposed methods of the challenge and several methods in previous works on the proposed LDV dataset.
1 code implementation • 27 Sep 2020 • Yannick Strümpler, Ren Yang, Radu Timofte
Therefore, we propose learning to improve the encoding performance with the standard decoder.
4 code implementations • 29 Jun 2020 • Ren Yang, Luc van Gool, Radu Timofte
At the time of writing this report, several learned video compression methods are superior to DVC, but currently none of them provides open source codes.
2 code implementations • 24 Jun 2020 • Ren Yang, Fabian Mentzer, Luc van Gool, Radu Timofte
The experiments show that our approach achieves the state-of-the-art learned video compression performance in terms of both PSNR and MS-SSIM.
3 code implementations • CVPR 2020 • Ren Yang, Fabian Mentzer, Luc van Gool, Radu Timofte
In our HLVC approach, the hierarchical quality benefits the coding efficiency, since the high quality information facilitates the compression and enhancement of low quality frames at encoder and decoder sides, respectively.
1 code implementation • ICCV 2019 • Xin Deng, Ren Yang, Mai Xu, Pier Luigi Dragotti
In this paper, we propose a novel method based on wavelet domain style transfer (WDST), which achieves a better PD tradeoff than the GAN based methods.
1 code implementation • 11 Mar 2019 • Ren Yang, Xiaoyan Sun, Mai Xu, Wen-Jun Zeng
The past decade has witnessed great success in applying deep learning to enhance the quality of compressed video.
no code implementations • 5 Mar 2019 • Tianyi Li, Mai Xu, Ren Yang, Xiaoming Tao
High efficiency video coding (HEVC) has brought outperforming efficiency for video compression.
1 code implementation • 26 Feb 2019 • Qunliang Xing, Zhenyu Guan, Mai Xu, Ren Yang, Tie Liu, Zulin Wang
Finally, experiments validate the effectiveness and generalization ability of our MFQE approach in advancing the state-of-the-art quality enhancement of compressed video.
Ranked #5 on
Video Enhancement
on MFQE v2
2 code implementations • 9 Oct 2018 • Jiaxin Lu, Mai Xu, Ren Yang, Zulin Wang
In particular, we find that the high-level feature of scene category is rather correlated with outdoor natural scene memorability, and the deep features learnt by deep neural network (DNN) are also effective in predicting the memorability scores.
no code implementations • 27 Aug 2018 • Jiaxin Lu, Mai Xu, Ren Yang, Zulin Wang
Recent studies on image memorability have shed light on the visual features that make generic images, object images or face photographs memorable.
1 code implementation • CVPR 2018 • Ren Yang, Mai Xu, Zulin Wang, Tianyi Li
In this paper, we investigate that heavy quality fluctuation exists across compressed video frames, and thus low quality frames can be enhanced using the neighboring high quality frames, seen as Multi-Frame Quality Enhancement (MFQE).
Ranked #6 on
Video Enhancement
on MFQE v2
no code implementations • 20 Sep 2017 • Ren Yang, Mai Xu, Tie Liu, Zulin Wang, Zhenyu Guan
Our experimental results validate that our QE-CNN method is effective in enhancing quality for both I and P frames of HEVC videos.
Multimedia
1 code implementation • 19 Sep 2017 • Mai Xu, Tianyi Li, Zulin Wang, Xin Deng, Ren Yang, Zhenyu Guan
Therefore, this paper proposes a deep learning approach to predict the CU partition for reducing the HEVC complexity at both intra- and inter-modes, which is based on convolutional neural network (CNN) and long- and short-term memory (LSTM) network.