VOC2012 Action Classification
2D Box
Action/Event Detection
License: Custom


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.


Please use the following citation when referencing the dataset:

author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",
title = "The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2012 {(VOC2012)} {R}esults",
howpublished = "http://www.pascal-network.org/challenges/VOC/voc2012/workshop/index.html"}



Data Summary
Provided by
The PASCAL Visual Object Classes
Pattern Analysis, Statistical Modelling and Computational learning.
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