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VOC2012 Action Classification

VOC2012 Action Classification

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Others 2D Box,Classification

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    README.md

    The main goal of this challenge is to recognize objects from a number of visual object classes in realistic scenes (i.e. not pre-segmented objects). It is fundamentally a supervised learning learning problem in that a training set of labelled images is provided. The twenty object classes that have been selected are:

    • Person: person
    • Animal: bird, cat, cow, dog, horse, sheep
    • Vehicle: aeroplane, bicycle, boat, bus, car, motorbike, train
    • Indoor: bottle, chair, dining table, potted plant, sofa, tv/monitor

    There are three main object recognition competitions: classification, detection, and segmentation, a competition on action classification, and a competition on large scale recognition run by ImageNet. In addition there is a "taster" competition on person layout.

    Action Classification Competition

    • Action Classification: Predicting the action(s) being performed by a person in a still image.

    In 2012 there are two variations of this competition, depending on how the person whose actions are to be classified is identified in a test image: (i) by a tight bounding box around the person; (ii) by only a single point located somewhere on the body. The latter competition aims to investigate the performance of methods given only approximate localization of a person, as might be the output from a generic person detector.

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