ImageNet 大规模视觉识别挑战赛
计算机视觉与模式识别
2015-02-02 v3
摘要
ImageNet 大规模视觉识别挑战赛是涵盖数百个物体类别和数百万张图像的物体分类与检测基准。该挑战赛自 2010 年起每年举办，吸引了五十多个机构的参与。本文描述了该基准数据集的构建，以及由此推动的物体识别进展。我们讨论了收集大规模真实标注（ground truth annotation）所面临的挑战，强调了类别物体识别的关键突破，提供了对大规模图像分类和物体检测领域现状的详细分析，并将最先进的计算机视觉精度与人类精度进行了比较。最后，我们总结了挑战赛五年来的经验教训，并提出了未来的方向和改进建议。
引用
@article{arxiv.1409.0575,
title = {ImageNet Large Scale Visual Recognition Challenge},
author = {Olga Russakovsky and Jia Deng and Hao Su and Jonathan Krause and Sanjeev Satheesh and Sean Ma and Zhiheng Huang and Andrej Karpathy and Aditya Khosla and Michael Bernstein and Alexander C. Berg and Li Fei-Fei},
journal= {arXiv preprint arXiv:1409.0575},
year = {2015}
}
备注
43 pages, 16 figures. v3 includes additional comparisons with PASCAL VOC (per-category comparisons in Table 3, distribution of localization difficulty in Fig 16), a list of queries used for obtaining object detection images (Appendix C), and some additional references