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

Overview

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.

Data Preview

Label Distribution

Citation

Please use the following citation when referencing the dataset:

@misc{pascal-voc-2012,
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"}

License

Custom

Data Summary
Type
Image,
Amount
17.125K
Size
1.86GB
Provided by
The PASCAL Visual Object Classes
Pattern Analysis, Statistical Modelling and Computational learning.
| Amount 17.125K | Size 1.86GB
VOC2012 Action Classification
2D Box Classification
Action/Event Detection
License: Custom

Overview

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.

Data Preview

Label Distribution

Citation

Please use the following citation when referencing the dataset:

@misc{pascal-voc-2012,
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"}

License

Custom

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