1 code implementation • 8 May 2024 • Yaqi Wu, Zhihao Fan, Xiaofeng Chu, Jimmy S. Ren, Xiaoming Li, Zongsheng Yue, Chongyi Li, Shangcheng Zhou, Ruicheng Feng, Yuekun Dai, Peiqing Yang, Chen Change Loy, Senyan Xu, Zhijing Sun, Jiaying Zhu, Yurui Zhu, Xueyang Fu, Zheng-Jun Zha, Jun Cao, Cheng Li, Shu Chen, Liang Ma, Shiyang Zhou, Haijin Zeng, Kai Feng, Yongyong Chen, Jingyong Su, Xianyu Guan, Hongyuan Yu, Cheng Wan, Jiamin Lin, Binnan Han, Yajun Zou, Zhuoyuan Wu, Yuan Huang, Yongsheng Yu, Daoan Zhang, Jizhe Li, Xuanwu Yin, Kunlong Zuo, Yunfan Lu, Yijie Xu, Wenzong Ma, Weiyu Guo, Hui Xiong, Wei Yu, Bingchun Luo, Sabari Nathan, Priya Kansal
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
no code implementations • CVPR 2024 • Yixin Yang, Jinxiu Liang, Bohan Yu, Yan Chen, Jimmy S. Ren, Boxin Shi
Event cameras with their high temporal resolution dynamic range and low power consumption are particularly good at time-sensitive applications like deblurring and frame interpolation.
2 code implementations • 8 Sep 2023 • Xiangyu Chen, Zheyuan Li, Zhengwen Zhang, Jimmy S. Ren, Yihao Liu, Jingwen He, Yu Qiao, Jiantao Zhou, Chao Dong
However, most resources are still in standard dynamic range (SDR).
no code implementations • CVPR 2023 • ZHIYANG YU, Yu Zhang, Dongqing Zou, Xijun Chen, Jimmy S. Ren, Shunqing Ren
Continuous-time video frame interpolation is a fundamental technique in computer vision for its flexibility in synthesizing motion trajectories and novel video frames at arbitrary intermediate time steps.
no code implementations • 1 Nov 2022 • Jinjin Gu, Jinan Zhou, Ringo Sai Wo Chu, Yan Chen, Jiawei Zhang, Xuanye Cheng, Song Zhang, Jimmy S. Ren
Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes in microsecond accuracy with a high dynamic range and low power consumption.
no code implementations • 23 Jun 2022 • Jinjin Gu, Haoming Cai, Chao Dong, Jimmy S. Ren, Radu Timofte
This challenge is divided into two tracks, a full-reference IQA track similar to the previous NTIRE IQA challenge and a new track that focuses on the no-reference IQA methods.
1 code implementation • ICCV 2021 • Xiangyu Chen, Zhengwen Zhang, Jimmy S. Ren, Lynhoo Tian, Yu Qiao, Chao Dong
However, most available resources are still in standard dynamic range (SDR).
no code implementations • CVPR 2021 • Liang Chen, Jiawei Zhang, Songnan Lin, Faming Fang, Jimmy S. Ren
To address this problem, we introduce a new blur model to fit both saturated and unsaturated pixels, and all informative pixels can be considered during deblurring process.
no code implementations • CVPR 2021 • Liang Chen, Jiawei Zhang, Jinshan Pan, Songnan Lin, Faming Fang, Jimmy S. Ren
Deblurring night blurry images is difficult, because the common-used blur model based on the linear convolution operation does not hold in this situation due to the influence of saturated pixels.
no code implementations • 7 May 2021 • Jinjin Gu, Haoming Cai, Chao Dong, Jimmy S. Ren, Yu Qiao, Shuhang Gu, Radu Timofte, Manri Cheon, SungJun Yoon, Byungyeon Kang, Junwoo Lee, Qing Zhang, Haiyang Guo, Yi Bin, Yuqing Hou, Hengliang Luo, Jingyu Guo, ZiRui Wang, Hai Wang, Wenming Yang, Qingyan Bai, Shuwei Shi, Weihao Xia, Mingdeng Cao, Jiahao Wang, Yifan Chen, Yujiu Yang, Yang Li, Tao Zhang, Longtao Feng, Yiting Liao, Junlin Li, William Thong, Jose Costa Pereira, Ales Leonardis, Steven McDonagh, Kele Xu, Lehan Yang, Hengxing Cai, Pengfei Sun, Seyed Mehdi Ayyoubzadeh, Ali Royat, Sid Ahmed Fezza, Dounia Hammou, Wassim Hamidouche, Sewoong Ahn, Gwangjin Yoon, Koki Tsubota, Hiroaki Akutsu, Kiyoharu Aizawa
This paper reports on the NTIRE 2021 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2021.
1 code implementation • ICCV 2021 • ZHIYANG YU, Yu Zhang, Deyuan Liu, Dongqing Zou, Xijun Chen, Yebin Liu, Jimmy S. Ren
Though trained on low frame-rate videos, our framework outperforms existing models trained with full high frame-rate videos (and events) on both GoPro dataset and a new real event-based dataset.
1 code implementation • ICCV 2021 • Wei Shang, Dongwei Ren, Dongqing Zou, Jimmy S. Ren, Ping Luo, WangMeng Zuo
EFM can also be easily incorporated into existing deblurring networks, making event-driven deblurring task benefit from state-of-the-art deblurring methods.
no code implementations • ECCV 2020 • Jianbo Liu, Junjun He, Jiawei Zhang, Jimmy S. Ren, Hongsheng Li
State-of-the-art semantic segmentation algorithms are mostly based on dilated Fully Convolutional Networks (dilatedFCN), which adopt dilated convolutions in the backbone networks to extract high-resolution feature maps for achieving high-performance segmentation performance.
no code implementations • ECCV 2020 • Jianbo Liu, Junjun He, Jimmy S. Ren, Yu Qiao, Hongsheng Li
Long-range contextual information is essential for achieving high-performance semantic segmentation.
1 code implementation • 7 May 2019 • Guocheng Qian, Yuanhao Wang, Jinjin Gu, Chao Dong, Wolfgang Heidrich, Bernard Ghanem, Jimmy S. Ren
In this work, we comprehensively study the effects of pipelines on the mixture problem of learning-based DN, DM, and SR, in both sequential and joint solutions.
1 code implementation • 11 Apr 2019 • Luyang Wang, Yan Chen, Zhenhua Guo, Keyuan Qian, Mude Lin, Hongsheng Li, Jimmy S. Ren
We observe that recent innovation in this area mainly focuses on new techniques that explicitly address the generalization issue when using this dataset, because this database is constructed in a highly controlled environment with limited human subjects and background variations.
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