Small Object Dataset
Zheng Ma and Lei Yu and Antoni B. Chan

@article{,
title= {Small Object Dataset},
keywords= {},
author= {Zheng Ma and Lei Yu and Antoni B. Chan},
abstract= {Images of small objects for small instance detections.  Currently four object types are available.

![](http://visal.cs.cityu.edu.hk/wp/wp-content/uploads/smallobject.jpg)

We collect four datasets of small objects from images/videos
on the Internet (e.g.YouTube or Google).

Fly Dataset: contains 600 video frames with an average
of 86 ± 39 flies per frame (648×72 @ 30 fps). 32 images
are used for training (1:6:187) and 50 images for testing
(301:6:600).

Honeybee Dataset: contains 118 images with an average
of 28 ± 6 honeybees per image (640×480). The dataset is
divided evenly for training and test sets. Only the first 32
images are used for training.

Fish Dataset: contains 387 frames of video with an average
of 56±9 fish per frame (300×410 @ 30 fps). 32 images
are used for training (1:3:94) and 65 for testing (193:3:387).

Seagull Dataset: contains three high-resolution images
(624×964) with an average of 866±107 seagulls per image.
The first image is used for training, and the rest for testing.

Cite this paper: http://visal.cs.cityu.edu.hk/static/pubs/conf/cvpr15-densdet.pdf
},
terms= {},
license= {},
superseded= {},
url= {http://visal.cs.cityu.edu.hk/downloads/smallobjects/}
}