VideoToStill StillToStill Face Recognition dataset
Datacite citation style:
Chen, Po-Shin (2019): VideoToStill StillToStill Face Recognition dataset. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:abade25d-19fc-43c9-8b86-28d9a840fb2c
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
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licence
CC0
This is the lists for our created large scale video-to-still (still-to-still) face recognition dataset, which combined MS1MV2 dataset (https://github.com/deepinsight/insightface/wiki/Dataset-Zoo) and COX dataset (http://vipl.ict.ac.cn/view_database.php?id=3).
For people who would like to use this lists to repeat our work, please sign the release agreement of COX dataset and cite all related papers/thesis.
history
- 2019-07-24 first online, published, posted
publisher
4TU.Centre for Research Data
format
media types: application/zip, text/plain, text/x-python
references
- http://vipl.ict.ac.cn/view_database.php?id=3
- https://arxiv.org/abs/1607.05427
- https://arxiv.org/abs/1801.07698
- https://github.com/deepinsight/insightface/wiki/Dataset-Zoo
- https://ieeexplore.ieee.org/document/7302053
- https://ieeexplore.ieee.org/document/7966443
- https://www.microsoft.com/en-us/research/project/ms-celeb-1m-challenge-recognizing-one-million-celebrities-real-world/
- https://www.researchgate.net/publication/295074418_MS-Celeb-1M_Challenge_of_Recognizing_One_Million_Celebrities_in_the_Real_World
organizations
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Software Technology
DATA
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