User:Datakeeper/DatasetsOnDeck
The purpose of this page is to curate datasets before putting them on pages like List of datasets for machine learning research.
| Dataset Name | Brief description | Preprocessing | Instances | Format | Default Task | Created (updated) | Reference | Creator |
|---|---|---|---|---|---|---|---|---|
| PASCAL VOC | Large number of images for classification tasks. | Labeling, bounding box included | 500,000 | Images, text | Classificaiton, object detection | 2010 | [1][2] | M. Everingham et al. |
| UCF 101 | Self described as "a dataset of 101 human actions classes from videos in the wild." Dataset is large with over 27 hours of video. | Actions classified and labeled. | 13,000 | Video, images, text | Classification, action detection | 2012 | [3][4] | K. Soomro et al. |
| THUMOS | Large video dataset for action classification. | Actions classified and labeled. | 45M frames of video | Video, images, text | Classification, action detection | 2013 | [5][6] | Y. Jiang et al. |
| German Traffic Sign Detection Benchmark Dataset | Images from vehicles of traffic signs on German roads. These signs comply with UN standards and therefore are the same as in other countries. | Signs manually labeled | 900 | Images | Classification | 2013 | [7][8] | S Houben et al. |
References
- ^ Everingham, Mark, et al. "The pascal visual object classes (voc) challenge."International journal of computer vision 88.2 (2010): 303-338.
- ^ Felzenszwalb, Pedro F., et al. "Object detection with discriminatively trained part-based models." Pattern Analysis and Machine Intelligence, IEEE Transactions on 32.9 (2010): 1627-1645.
- ^ Soomro, Khurram, Amir Roshan Zamir, and Mubarak Shah. "UCF101: A dataset of 101 human actions classes from videos in the wild." arXiv preprint arXiv:1212.0402 (2012).
- ^ Karpathy, Andrej, et al. "Large-scale video classification with convolutional neural networks." Proceedings of the IEEE conference on Computer Vision and Pattern Recognition. 2014.
- ^ Jiang, Y. G., et al. "THUMOS challenge: Action recognition with a large number of classes." ICCV Workshop on Action Recognition with a Large Number of Classes, http://crcv. ucf. edu/ICCV13-Action-Workshop. 2013.
- ^ Simonyan, Karen, and Andrew Zisserman. "Two-stream convolutional networks for action recognition in videos." Advances in Neural Information Processing Systems. 2014.
- ^ Houben, Sebastian, et al. "Detection of traffic signs in real-world images: The German Traffic Sign Detection Benchmark." Neural Networks (IJCNN), The 2013 International Joint Conference on. IEEE, 2013.
- ^ Mathias, Mayeul, et al. "Traffic sign recognition—How far are we from the solution?." Neural Networks (IJCNN), The 2013 International Joint Conference on. IEEE, 2013.