mlsanityData to 14 Oct 2026

NTIRE 2024 Quality Assessment of AI-Generated Content Challenge

arXiv 2404.16687 ↗First posted 25 Apr 2024cs.CVcited by 20

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Abstract (arXiv)

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.

Key facts. Cited by 20 papers in the map (data through 14 Oct 2026). Builds on 102 of its 126 references that are in the map. First posted on arXiv 25 Apr 2024.

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102 of 126 references.

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Citing papers per year: 2024: 10; 2025: 9; 2026: 1.

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  1. 2024Fr'echet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videoscited by 58
  2. 2024Q-Bench-Video: Benchmarking the Video Quality Understanding of LMMscited by 39
  3. 2024Quality Assessment in the Era of Large Models: A Surveycited by 26
  4. 2024PPLLaVA: Varied Video Sequence Understanding With Prompt Guidancecited by 20
  5. 2025Image Quality Assessment: From Human to Machine Preferencecited by 12
  6. 2024AltGen: AI-Driven Alt Text Generation for Enhancing EPUB Accessibilitycited by 11
  7. 2024NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challengecited by 9
  8. 2025Flow4Agent: Long-form Video Understanding via Motion Prior from Optical Flowcited by 9
  9. 2024G-Refine: A General Quality Refiner for Text-to-Image Generationcited by 8
  10. 2024CMC-Bench: Towards a New Paradigm of Visual Signal Compressioncited by 6
  11. 2024NTIRE 2024 Challenge on Night Photography Renderingcited by 4
  12. 2025VF-Eval: Evaluating Multimodal LLMs for Generating Feedback on AIGC Videoscited by 4
8 more
  1. 2025Q-Save: Towards Scoring and Attribution for Generated Video Evaluationcited by 4
  2. 2025Multilevel Semantic-Aware Model for AI-Generated Video Quality Assessmentcited by 2
  3. 2025M3-AGIQA: Multimodal, Multi-Round, Multi-Aspect AI-Generated Image Quality Assessmentcited by 2
  4. 2025GeneVA: A Dataset of Human Annotations for Generative Text to Video Artifactscited by 2
  5. 2026RL-ScanIQA: Reinforcement-Learned Scanpaths for Blind 360degImage Quality Assessmentcited by 2
  6. 2025RAISE: Realness Assessment for Image Synthesis and Evaluationcited by 1
  7. 2025IE-Critic-R1: Advancing the Explanatory Measurement of Text-Driven Image Editing for Human Perception Alignmentcited by 1
  8. 2024NTIRE 2024 Challenge on Stereo Image Super-Resolution: Methods and Resultscited by 0