  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.
