Kavli Affiliate: Jia Liu
| First 5 Authors: Xiaohong Liu, Xiongkuo Min, Qiang Hu, Xiaoyun Zhang, Jie Guo
| Summary:
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.
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