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INRIA Holidays Dataset
2D Classification
许可协议: Unknown

Overview

The Holidays dataset is a set of images which mainly contains some of our personal holidays photos. The remaining ones were taken on purpose to test the robustness to various attacks: rotations, viewpoint and illumination changes, blurring, etc. The dataset includes a very large variety of scene types (natural, man-made, water and fire effects, etc) and images are in high resolution. The dataset contains 500 image groups, each of which represents a distinct scene or object. The first image of each group is the query image and the correct retrieval results are the other images of the group.

The dataset can be downloaded from this page, see details below. The material given includes:

  • the images themselves.
  • the set of descriptors extracted from these images (see details below).
  • a set of descriptors produced, with the same extractor and descriptor, for a distinct dataset (Flickr60K).
  • two sets of clusters used to quantize the descriptors. These have been obtained from Flickr60K.
  • some pre-processed feature files for one million images, that we have used in our ECCV paper to perform the evaluation on a large scale.
数据概要
数据格式
image,
数据量
1.491K
文件大小
--
| 数据量 1.491K | 大小 --
INRIA Holidays Dataset
2D Classification
许可协议: Unknown

Overview

The Holidays dataset is a set of images which mainly contains some of our personal holidays photos. The remaining ones were taken on purpose to test the robustness to various attacks: rotations, viewpoint and illumination changes, blurring, etc. The dataset includes a very large variety of scene types (natural, man-made, water and fire effects, etc) and images are in high resolution. The dataset contains 500 image groups, each of which represents a distinct scene or object. The first image of each group is the query image and the correct retrieval results are the other images of the group.

The dataset can be downloaded from this page, see details below. The material given includes:

  • the images themselves.
  • the set of descriptors extracted from these images (see details below).
  • a set of descriptors produced, with the same extractor and descriptor, for a distinct dataset (Flickr60K).
  • two sets of clusters used to quantize the descriptors. These have been obtained from Flickr60K.
  • some pre-processed feature files for one million images, that we have used in our ECCV paper to perform the evaluation on a large scale.
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