In this report, we introduce NICE project\footnote{\url{https://nice.lgresearch.ai/}} and share the results and outcomes of NICE challenge 2023. This project is designed to challenge the computer vision community to develop robust image captioning models that advance the state-of-the-art both in terms of accuracy and fairness. Through the challenge, the image captioning models were tested using a new evaluation dataset that includes a large variety of visual concepts from many domains. There was no specific training data provided for the challenge, and therefore the challenge entries were required to adapt to new types of image descriptions that had not been seen during training. This report includes information on the newly proposed NICE dataset, evaluation methods, challenge results, and technical details of top-ranking entries. We expect that the outcomes of the challenge will contribute to the improvement of AI models on various vision-language tasks.

翻译：本报告介绍了NICE项目\footnote{\url{https://nice.lgresearch.ai/}}并分享了NICE 2023挑战赛的结果与成果。该项目旨在激励计算机视觉领域的研究社区开发兼具高精度与公平性的鲁棒图像描述模型。挑战赛通过包含多领域广泛视觉概念的新评估数据集对图像描述模型进行测试。由于未提供特定训练数据，参赛模型必须适应训练阶段未曾见过的新型图像描述。本报告涵盖新提出的NICE数据集、评估方法、挑战赛结果以及排名靠前的参赛作品技术细节。我们期望该挑战赛的成果能够推动各类视觉-语言任务中AI模型的改进。