Zobrazeno 1 - 10
of 546
pro vyhledávání: '"Liu Jianzhao"'
Autor:
Molodetskikh, Ivan, Borisov, Artem, Vatolin, Dmitriy, Timofte, Radu, Liu, Jianzhao, Zhi, Tianwu, Zhang, Yabin, Li, Yang, Xu, Jingwen, Liao, Yiting, Luo, Qing, Zhang, Ao-Xiang, Zhang, Peng, Lei, Haibo, Jiang, Linyan, Li, Yaqing, Cao, Yuqin, Sun, Wei, Zhang, Weixia, Sun, Yinan, Jia, Ziheng, Zhu, Yuxin, Min, Xiongkuo, Zhai, Guangtao, Luo, Weihua, Z., Yupeng, Y, Hong
This paper presents the Video Super-Resolution (SR) Quality Assessment (QA) Challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2024. The task of this challenge was to develop an objective QA me
Externí odkaz:
http://arxiv.org/abs/2410.04225
Autor:
Liu, Xiaohong, Min, Xiongkuo, Zhai, Guangtao, Li, Chunyi, Kou, Tengchuan, Sun, Wei, Wu, Haoning, Gao, Yixuan, Cao, Yuqin, Zhang, Zicheng, Wu, Xiele, Timofte, Radu, Peng, Fei, Fu, Huiyuan, Ming, Anlong, Wang, Chuanming, Ma, Huadong, He, Shuai, Dou, Zifei, Chen, Shu, Zhang, Huacong, Xie, Haiyi, Wang, Chengwei, Chen, Baoying, Zeng, Jishen, Yang, Jianquan, Wang, Weigang, Fang, Xi, Lv, Xiaoxin, Yan, Jun, Zhi, Tianwu, Zhang, Yabin, Li, Yaohui, Li, Yang, Xu, Jingwen, Liu, Jianzhao, Liao, Yiting, Li, Junlin, Yu, Zihao, Lu, Yiting, Li, Xin, Motamednia, Hossein, Hosseini-Benvidi, S. Farhad, Guan, Fengbin, Mahmoudi-Aznaveh, Ahmad, Mansouri, Azadeh, Gankhuyag, Ganzorig, Yoon, Kihwan, Xu, Yifang, Fan, Haotian, Kong, Fangyuan, Zhao, Shiling, Dong, Weifeng, Yin, Haibing, Zhu, Li, Wang, Zhiling, Huang, Bingchen, Saha, Avinab, Mishra, Sandeep, Gupta, Shashank, Sureddi, Rajesh, Saha, Oindrila, Celona, Luigi, Bianco, Simone, Napoletano, Paolo, Schettini, Raimondo, Yang, Junfeng, Fu, Jing, Zhang, Wei, Cao, Wenzhi, Liu, Limei, Peng, Han, Yuan, Weijun, Li, Zhan, Cheng, Yihang, Deng, Yifan, Li, Haohui, Qu, Bowen, Li, Yao, Luo, Shuqing, Wang, Shunzhou, Gao, Wei, Lu, Zihao, Conde, Marcos V., Wang, Xinrui, Chen, Zhibo, Liao, Ruling, Ye, Yan, Wang, Qiulin, Li, Bing, Zhou, Zhaokun, Geng, Miao, Chen, Rui, Tao, Xin, Liang, Xiaoyu, Sun, Shangkun, Ma, Xingyuan, Li, Jiaze, Yang, Mengduo, Xu, Haoran, Zhou, Jie, Zhu, Shiding, Yu, Bohan, Chen, Pengfei, Xu, Xinrui, Shen, Jiabin, Duan, Zhichao, Asadi, Erfan, Liu, Jiahe, Yan, Qi, Qu, Youran, Zeng, Xiaohui, Wang, Lele, Liao, Renjie
This paper reports on the NTIRE 2024 Quality Assessment of AI-Generated Content Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2024. This challenge is to address a major
Externí odkaz:
http://arxiv.org/abs/2404.16687
StyleAM: Perception-Oriented Unsupervised Domain Adaption for Non-reference Image Quality Assessment
Deep neural networks (DNNs) have shown great potential in non-reference image quality assessment (NR-IQA). However, the annotation of NR-IQA is labor-intensive and time-consuming, which severely limits their application especially for authentic image
Externí odkaz:
http://arxiv.org/abs/2207.14489
Existing learning-based methods for blind image quality assessment (BIQA) are heavily dependent on large amounts of annotated training data, and usually suffer from a severe performance degradation when encountering the domain/distribution shift prob
Externí odkaz:
http://arxiv.org/abs/2207.08124
Image compression has raised widespread interest recently due to its significant importance for multimedia storage and transmission. Meanwhile, a reliable image quality assessment (IQA) for compressed images can not only help to verify the performanc
Externí odkaz:
http://arxiv.org/abs/2205.04264
Publikováno v:
In Trends in Cell Biology May 2024 34(5):355-359
Autor:
Deng, Xumeng, Chen, Kaihao, Pang, Kai, Liu, Xiaoting, Gao, Minsong, Ren, Jie, Yang, Guanwen, Wu, Guangpeng, Zhang, Chengjian, Ni, Xufeng, Zhang, Peng, Ji, Jian, Liu, Jianzhao, Mao, Zhengwei, Wu, Ziliang, Xu, Zhen, Zhang, Haoke, Li, Hanying
Publikováno v:
In Chinese Chemical Letters March 2024 35(3)
Existing blind image quality assessment (BIQA) methods are mostly designed in a disposable way and cannot evolve with unseen distortions adaptively, which greatly limits the deployment and application of BIQA models in real-world scenarios. To addres
Externí odkaz:
http://arxiv.org/abs/2104.14115
Autor:
Wang, Nannan, Li, Kexin, Yuan, Fenghui, Zuo, Yunjiang, Liu, Jianzhao, Zhu, Xinhao, Sun, Ying, Guo, Ziyu, Zhang, Lihua, Gong, Chao, Song, Yanyu, Song, Changchun, Xu, Xiaofeng
Publikováno v:
In Soil Biology and Biochemistry February 2024 189
Autor:
Guo, Ziyu, Wang, Yihui, Liu, Jianzhao, He, Liyuan, Zhu, Xinhao, Zuo, Yunjiang, Wang, Nannan, Yuan, Fenghui, Sun, Ying, Zhang, Lihua, Song, Yanyu, Song, Changchun, Xu, Xiaofeng
Publikováno v:
In Science of the Total Environment 1 January 2024 906