MARC21: :: Library Catalog

Salvato in:

Dettagli Bibliografici
Autori principali:	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
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	https://arxiv.org/abs/2404.16687
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

_version_	1866910437013979136
author	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
author_facet	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
contents	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 Content (AIGC). The challenge is divided into the image track and the video track. The image track uses the AIGIQA-20K, which contains 20,000 AI-Generated Images (AIGIs) generated by 15 popular generative models. The image track has a total of 318 registered participants. A total of 1,646 submissions are received in the development phase, and 221 submissions are received in the test phase. Finally, 16 participating teams submitted their models and fact sheets. The video track uses the T2VQA-DB, which contains 10,000 AI-Generated Videos (AIGVs) generated by 9 popular Text-to-Video (T2V) models. A total of 196 participants have registered in the video track. A total of 991 submissions are received in the development phase, and 185 submissions are received in the test phase. Finally, 12 participating teams submitted their models and fact sheets. Some methods have achieved better results than baseline methods, and the winning methods in both tracks have demonstrated superior prediction performance on AIGC.
format	Preprint
id	arxiv_https___arxiv_org_abs_2404_16687
institution	arXiv
publishDate	2024
record_format	arxiv
spellingShingle	NTIRE 2024 Quality Assessment of AI-Generated Content Challenge 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 Computer Vision and Pattern Recognition 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 Content (AIGC). The challenge is divided into the image track and the video track. The image track uses the AIGIQA-20K, which contains 20,000 AI-Generated Images (AIGIs) generated by 15 popular generative models. The image track has a total of 318 registered participants. A total of 1,646 submissions are received in the development phase, and 221 submissions are received in the test phase. Finally, 16 participating teams submitted their models and fact sheets. The video track uses the T2VQA-DB, which contains 10,000 AI-Generated Videos (AIGVs) generated by 9 popular Text-to-Video (T2V) models. A total of 196 participants have registered in the video track. A total of 991 submissions are received in the development phase, and 185 submissions are received in the test phase. Finally, 12 participating teams submitted their models and fact sheets. Some methods have achieved better results than baseline methods, and the winning methods in both tracks have demonstrated superior prediction performance on AIGC.
title	NTIRE 2024 Quality Assessment of AI-Generated Content Challenge
topic	Computer Vision and Pattern Recognition
url	https://arxiv.org/abs/2404.16687

Documenti analoghi