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NTIRE 2024 Quality Assessment of AI-Generated Content Challenge
Xiaohong Liu;Xiongkuo Min;Guangtao Zhai;Chunyi Li;Tengchuan Kou;Wei Sun;Haoning Wu;Yixuan Gao;Yuqin Cao;Zicheng Zhang;Xiele Wu;Radu Timofte;Fei Peng;Huiyuan Fu;Anlong Ming;Chuanming Wang;Huadong Ma;Shuai He;Zifei Dou;Shu Chen;Huacong Zhang;Haiyi Xie;Chengwei Wang;Baoying Chen;Jishen Zeng;Jianquan Yang;Weigang Wang;Xi Fang;Xiaoxin Lv;Jun Yan;Tianwu Zhi;Yabin Zhang;Yaohui Li;Yang Li;Jingwen Xu;Jianzhao Liu;Yiting Liao;Junlin Li;Zihao Yu;Fengbin Guan;Yiting Lu;Xin Li;Hossein Motamednia;S. Farhad Hosseini-Benvidi;Ahmad Mahmoudi-Aznaveh;Azadeh Mansouri;Ganzorig Gankhuyag;Kihwan Yoon;Yifang Xu;Haotian Fan;Fangyuan Kong;Shiling Zhao;Weifeng Dong;Haibing Yin;Li Zhu;Zhiling Wang;Bingchen Huang;Avinab Saha;Sandeep Mishra;Shashank Gupta;Rajesh Sureddi;Oindrila Saha;Luigi Celona;Simone Bianco;Paolo Napoletano;Raimondo Schettini;Junfeng Yang;Jing Fu;Wei Zhang;Wenzhi Cao;Limei Liu;Han Peng;Weijun Yuan;Zhan Li;Yihang Cheng;Yifan Deng;Haohui Li;Bowen Qu;Yao Li;Shuqing Luo;Shunzhou Wang;Wei Gao;Zihao Lu;Marcos V. Conde;Radu Timofte;Xinrui Wang;Zhibo Chen;Ruling Liao;Yan Ye;Qiulin Wang;Bing Li;Zhaokun Zhou;Miao Geng;Rui Chen;Xin Tao;Xiaoyu Liang;Shangkun Sun;Xingyuan Ma;Jiaze Li;Mengduo Yang;Haoran Xu;Jie Zhou;Shiding Zhu;Bohan Yu;Pengfei Chen;Xinrui Xu;Jiabin Shen;Zhichao Duan;Erfan Asadi;Jiahe Liu;Qi Yan;Youran Qu;Xiaohui Zeng;Lele Wang;Renjie Liao
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2024 | Conference Paper |
Cited by: Papers (25)
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 challenge in the field of image and video processing, namely, Image Quality Assessment (IQA) and Video Quality Assessment (VQA) for AI-Generated Conte...Show More
NTIRE 2024 Quality Assessment of AI-Generated Content Challenge
Xiaohong Liu;Xiongkuo Min;Guangtao Zhai;Chunyi Li;Tengchuan Kou;Wei Sun;Haoning Wu;Yixuan Gao;Yuqin Cao;Zicheng Zhang;Xiele Wu;Radu Timofte;Fei Peng;Huiyuan Fu;Anlong Ming;Chuanming Wang;Huadong Ma;Shuai He;Zifei Dou;Shu Chen;Huacong Zhang;Haiyi Xie;Chengwei Wang;Baoying Chen;Jishen Zeng;Jianquan Yang;Weigang Wang;Xi Fang;Xiaoxin Lv;Jun Yan;Tianwu Zhi;Yabin Zhang;Yaohui Li;Yang Li;Jingwen Xu;Jianzhao Liu;Yiting Liao;Junlin Li;Zihao Yu;Fengbin Guan;Yiting Lu;Xin Li;Hossein Motamednia;S. Farhad Hosseini-Benvidi;Ahmad Mahmoudi-Aznaveh;Azadeh Mansouri;Ganzorig Gankhuyag;Kihwan Yoon;Yifang Xu;Haotian Fan;Fangyuan Kong;Shiling Zhao;Weifeng Dong;Haibing Yin;Li Zhu;Zhiling Wang;Bingchen Huang;Avinab Saha;Sandeep Mishra;Shashank Gupta;Rajesh Sureddi;Oindrila Saha;Luigi Celona;Simone Bianco;Paolo Napoletano;Raimondo Schettini;Junfeng Yang;Jing Fu;Wei Zhang;Wenzhi Cao;Limei Liu;Han Peng;Weijun Yuan;Zhan Li;Yihang Cheng;Yifan Deng;Haohui Li;Bowen Qu;Yao Li;Shuqing Luo;Shunzhou Wang;Wei Gao;Zihao Lu;Marcos V. Conde;Radu Timofte;Xinrui Wang;Zhibo Chen;Ruling Liao;Yan Ye;Qiulin Wang;Bing Li;Zhaokun Zhou;Miao Geng;Rui Chen;Xin Tao;Xiaoyu Liang;Shangkun Sun;Xingyuan Ma;Jiaze Li;Mengduo Yang;Haoran Xu;Jie Zhou;Shiding Zhu;Bohan Yu;Pengfei Chen;Xinrui Xu;Jiabin Shen;Zhichao Duan;Erfan Asadi;Jiahe Liu;Qi Yan;Youran Qu;Xiaohui Zeng;Lele Wang;Renjie Liao
Year: 2024 | Conference Paper |
GraphProxy: Communication-Efficient Federated Graph Learning with Adaptive Proxy
Junyang Wang;Lan Zhang;Junhao Wang;Mu Yuan;Yihang Cheng;Qian Xu;Bo Yu
IEEE INFOCOM 2024 - IEEE Conference on Computer Communications
Year: 2024 | Conference Paper |
Federated graph learning (FGL) enables multiple participants with distributed but connected graph data to collaboratively train a model in a privacy-preserving way. However, the high communication cost hinder the adoption of FGL in many resource-limited or delay-sensitive applications. In this work, we focus on reducing the communication cost incurred by the transmission of neighborhood informatio...Show More
FedMix: Boosting with Data Mixture for Vertical Federated Learning
Yihang Cheng;Lan Zhang;Junyang Wang;Xiaokai Chu;Dongbo Huang;Lan Xu
2024 IEEE 40th International Conference on Data Engineering (ICDE)
Year: 2024 | Conference Paper |
Cited by: Papers (1)
The need to safeguard data privacy and adhere to regulations such as GDPR creates data silos and has prompted the emergence and widespread adoption of techniques for distributed databases. To effectively explore the value of data across multiple organizations, techniques for data management, data analysis and data functionality from distributed databases have been proposed. Recently, Vertical Fede...Show More
TVFL: Tunable Vertical Federated Learning towards Communication-Efficient Model Serving
Junhao Wang;Lan Zhang;Yihang Cheng;Shaoang Li;Hong Zhang;Dongbo Huang;Xu Lan
IEEE INFOCOM 2023 - IEEE Conference on Computer Communications
Year: 2023 | Conference Paper |
Cited by: Papers (6)
Vertical federated learning (VFL) enables multiple participants with different data features and the same sample ID space to collaboratively train a model in a privacy-preserving way. However, the high computational and communication overheads hinder the adoption of VFL in many resource-limited or delay-sensitive applications. In this work, we focus on reducing the communication cost and delay inc...Show More
GFL: Federated Learning on Non-IID Data via Privacy-Preserving Synthetic Data
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Year: 2023 | Conference Paper |
Cited by: Papers (6)
Federated learning (FL) enables large amounts of participants to construct a global learning model, while storing training data privately at local client devices. A fundamental issue in FL systems is the susceptibility to the highly skewed distributed data. A series of methods have been proposed to mitigate the Non-IID problem by limiting the distances between local models and the global model, bu...Show More
What is Market Talking About? Market-Oriented Prospect Analysis for Entrepreneur Fundraising
Hongke Zhao;Yihang Cheng;Xi Zhang;Hengshu Zhu;Qi Liu;Hui Xiong;Wei Zhang
In recent decades, innovation and entrepreneurship have become buzz words. With entrepreneurial projects emerging in large numbers every day, the common intention of all investors, i.e., putting every penny into good entrepreneurial projects, is becoming more difficult. In reality, traditional research with empirical results is not practical for analyzing these newly launched projects of small and...Show More
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