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| Format: | Preprint |
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2025
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| Online-Zugang: | https://arxiv.org/abs/2506.02875 |
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| author | Liu, Xiaohong Min, Xiongkuo Hu, Qiang Zhang, Xiaoyun Guo, Jie Zhai, Guangtao Wang, Shushi Zhou, Yingjie Liu, Lu Li, Jingxin Yang, Liu Wen, Farong Xu, Li Jiang, Yanwei Zhu, Xilei Li, Chunyi Zhang, Zicheng Duan, Huiyu Wu, Xiele Gao, Yixuan Cao, Yuqin Jia, Jun Sun, Wei Cao, Jiezhang Timofte, Radu Li, Baojun Huang, Jiamian Luo, Dan Liu, Tao Zhang, Weixia Zheng, Bingkun Chen, Junlin Zhou, Ruikai Chen, Meiya Wang, Yu Jiang, Hao Li, Xiantao Jiang, Yuxiang Tang, Jun Zhao, Yimeng Hu, Bo Qi, Zelu Zhang, Chaoyang Zhao, Fei Shi, Ping Fu, Lingzhi Cong, Heng He, Shuai Zhang, Rongyu He, Jiarong Hu, Zongyao Luo, Wei Yu, Zihao Guan, Fengbin Lu, Yiting Li, Xin Chen, Zhibo Su, Mengjing Wang, Yi Chen, Tuo Li, Chunxiao Zhao, Shuaiyu Wen, Jiaxin Lin, Chuyi Liu, Sitong Chu, Ningxin Wan, Jing Zhou, Yu Chen, Baoying Zeng, Jishen Liu, Jiarui Liu, Xianjin Chen, Xin Zhou, Lanzhi Li, Hangyu Han, You Xiang, Bibo Liu, Zhenjie Lu, Jianzhang Gui, Jialin Lu, Renjie Wang, Shangfei Zhou, Donghao Lin, Jingyu Song, Quanjian Huang, Jiancheng Yang, Yufeng Wang, Changwei Zhong, Shupeng Yang, Yang He, Lihuo Liu, Jia Xing, Yuting Fang, Tida Jin, Yuchun |
| author_facet | Liu, Xiaohong Min, Xiongkuo Hu, Qiang Zhang, Xiaoyun Guo, Jie Zhai, Guangtao Wang, Shushi Zhou, Yingjie Liu, Lu Li, Jingxin Yang, Liu Wen, Farong Xu, Li Jiang, Yanwei Zhu, Xilei Li, Chunyi Zhang, Zicheng Duan, Huiyu Wu, Xiele Gao, Yixuan Cao, Yuqin Jia, Jun Sun, Wei Cao, Jiezhang Timofte, Radu Li, Baojun Huang, Jiamian Luo, Dan Liu, Tao Zhang, Weixia Zheng, Bingkun Chen, Junlin Zhou, Ruikai Chen, Meiya Wang, Yu Jiang, Hao Li, Xiantao Jiang, Yuxiang Tang, Jun Zhao, Yimeng Hu, Bo Qi, Zelu Zhang, Chaoyang Zhao, Fei Shi, Ping Fu, Lingzhi Cong, Heng He, Shuai Zhang, Rongyu He, Jiarong Hu, Zongyao Luo, Wei Yu, Zihao Guan, Fengbin Lu, Yiting Li, Xin Chen, Zhibo Su, Mengjing Wang, Yi Chen, Tuo Li, Chunxiao Zhao, Shuaiyu Wen, Jiaxin Lin, Chuyi Liu, Sitong Chu, Ningxin Wan, Jing Zhou, Yu Chen, Baoying Zeng, Jishen Liu, Jiarui Liu, Xianjin Chen, Xin Zhou, Lanzhi Li, Hangyu Han, You Xiang, Bibo Liu, Zhenjie Lu, Jianzhang Gui, Jialin Lu, Renjie Wang, Shangfei Zhou, Donghao Lin, Jingyu Song, Quanjian Huang, Jiancheng Yang, Yufeng Wang, Changwei Zhong, Shupeng Yang, Yang He, Lihuo Liu, Jia Xing, Yuting Fang, Tida Jin, Yuchun |
| contents | This paper reports on the NTIRE 2025 XGC Quality Assessment Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2025. This challenge is to address a major challenge in the field of video and talking head processing. The challenge is divided into three tracks, including user generated video, AI generated video and talking head. The user-generated video track uses the FineVD-GC, which contains 6,284 user generated videos. The user-generated video track has a total of 125 registered participants. A total of 242 submissions are received in the development phase, and 136 submissions are received in the test phase. Finally, 5 participating teams submitted their models and fact sheets. The AI generated video track uses the Q-Eval-Video, which contains 34,029 AI-Generated Videos (AIGVs) generated by 11 popular Text-to-Video (T2V) models. A total of 133 participants have registered in this track. A total of 396 submissions are received in the development phase, and 226 submissions are received in the test phase. Finally, 6 participating teams submitted their models and fact sheets. The talking head track uses the THQA-NTIRE, which contains 12,247 2D and 3D talking heads. A total of 89 participants have registered in this track. A total of 225 submissions are received in the development phase, and 118 submissions are received in the test phase. Finally, 8 participating teams submitted their models and fact sheets. Each participating team in every track has proposed a method that outperforms the baseline, which has contributed to the development of fields in three tracks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_02875 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | NTIRE 2025 XGC Quality Assessment Challenge: Methods and Results Liu, Xiaohong Min, Xiongkuo Hu, Qiang Zhang, Xiaoyun Guo, Jie Zhai, Guangtao Wang, Shushi Zhou, Yingjie Liu, Lu Li, Jingxin Yang, Liu Wen, Farong Xu, Li Jiang, Yanwei Zhu, Xilei Li, Chunyi Zhang, Zicheng Duan, Huiyu Wu, Xiele Gao, Yixuan Cao, Yuqin Jia, Jun Sun, Wei Cao, Jiezhang Timofte, Radu Li, Baojun Huang, Jiamian Luo, Dan Liu, Tao Zhang, Weixia Zheng, Bingkun Chen, Junlin Zhou, Ruikai Chen, Meiya Wang, Yu Jiang, Hao Li, Xiantao Jiang, Yuxiang Tang, Jun Zhao, Yimeng Hu, Bo Qi, Zelu Zhang, Chaoyang Zhao, Fei Shi, Ping Fu, Lingzhi Cong, Heng He, Shuai Zhang, Rongyu He, Jiarong Hu, Zongyao Luo, Wei Yu, Zihao Guan, Fengbin Lu, Yiting Li, Xin Chen, Zhibo Su, Mengjing Wang, Yi Chen, Tuo Li, Chunxiao Zhao, Shuaiyu Wen, Jiaxin Lin, Chuyi Liu, Sitong Chu, Ningxin Wan, Jing Zhou, Yu Chen, Baoying Zeng, Jishen Liu, Jiarui Liu, Xianjin Chen, Xin Zhou, Lanzhi Li, Hangyu Han, You Xiang, Bibo Liu, Zhenjie Lu, Jianzhang Gui, Jialin Lu, Renjie Wang, Shangfei Zhou, Donghao Lin, Jingyu Song, Quanjian Huang, Jiancheng Yang, Yufeng Wang, Changwei Zhong, Shupeng Yang, Yang He, Lihuo Liu, Jia Xing, Yuting Fang, Tida Jin, Yuchun Computer Vision and Pattern Recognition This paper reports on the NTIRE 2025 XGC Quality Assessment Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2025. This challenge is to address a major challenge in the field of video and talking head processing. The challenge is divided into three tracks, including user generated video, AI generated video and talking head. The user-generated video track uses the FineVD-GC, which contains 6,284 user generated videos. The user-generated video track has a total of 125 registered participants. A total of 242 submissions are received in the development phase, and 136 submissions are received in the test phase. Finally, 5 participating teams submitted their models and fact sheets. The AI generated video track uses the Q-Eval-Video, which contains 34,029 AI-Generated Videos (AIGVs) generated by 11 popular Text-to-Video (T2V) models. A total of 133 participants have registered in this track. A total of 396 submissions are received in the development phase, and 226 submissions are received in the test phase. Finally, 6 participating teams submitted their models and fact sheets. The talking head track uses the THQA-NTIRE, which contains 12,247 2D and 3D talking heads. A total of 89 participants have registered in this track. A total of 225 submissions are received in the development phase, and 118 submissions are received in the test phase. Finally, 8 participating teams submitted their models and fact sheets. Each participating team in every track has proposed a method that outperforms the baseline, which has contributed to the development of fields in three tracks. |
| title | NTIRE 2025 XGC Quality Assessment Challenge: Methods and Results |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2506.02875 |