作者
Fanda Fan, Chunjie Luo, Wanling Gao, Jianfeng Zhan
发表日期
2023/12/1
期刊
BenchCouncil Transactions on Benchmarks, Standards and Evaluations
卷号
3
期号
4
页码范围
100152
出版商
Elsevier
简介
The burgeoning field of Artificial Intelligence Generated Content (AIGC) is witnessing rapid advancements, particularly in video generation. This paper introduces AIGCBench, a pioneering comprehensive and scalable benchmark designed to evaluate a variety of video generation tasks, with a primary focus on Image-to-Video (I2V) generation. AIGCBench tackles the limitations of existing benchmarks, which suffer from a lack of diverse datasets, by including a varied and open-domain image–text dataset that evaluates different state-of-the-art algorithms under equivalent conditions. We employ a novel text combiner and GPT-4 to create rich text prompts, which are then used to generate images via advanced Text-to-Image models. To establish a unified evaluation framework for video generation tasks, our benchmark includes 11 metrics spanning four dimensions to assess algorithm performance. These dimensions …
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F Fan, C Luo, W Gao, J Zhan - BenchCouncil Transactions on Benchmarks, Standards …, 2023