The Pascal Visual Object Classes (VOC) Challenge
The Pascal Visual Object Classes (VOC) Challenge
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DOI：
10.1007/s11263-009-0275-4
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发表时间：
2010-06-10
影响因子：
19.5
通讯作者：
Zisserman, Andrew
中科院分区：
文献类型：
--
作者：
Everingham, Mark;Van Gool, Luc;Zisserman, Andrew
PASCAL视觉对象类(VOC)挑战是视觉对象类别识别和检测的基准，为视觉和机器学习团体提供了标准的图像和注释数据集，以及标准的评估程序。从2005年至今每年组织一次的挑战赛及其相关数据集已被公认为目标检测的基准。本文描述了数据集和评估程序。我们回顾了用于分类和检测的评估方法的最新进展，分析了这些方法是否在统计上不同，它们从图像中学习了什么(例如，对象或其上下文)，以及这些方法发现哪些容易或混淆。文章最后总结了三年来挑战的经验教训，并提出了未来改进和推广的方向。
The Pascal Visual Object Classes (VOC) challenge is a benchmark in visual object category recognition and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has become accepted as the benchmark for object detection.This paper describes the dataset and evaluation procedure. We review the state-of-the-art in evaluated methods for both classification and detection, analyse whether the methods are statistically different, what they are learning from the images (e.g. the object or its context), and what the methods find easy or confuse. The paper concludes with lessons learnt in the three year history of the challenge, and proposes directions for future improvement and extension.