VIPriors 1: Visual Inductive Priors for Data-Efficient Deep Learning Challenges [article]

Robert-Jan Bruintjes, Attila Lengyel, Marcos Baptista Rios, Osman Semih Kayhan, Jan van Gemert
2021 arXiv   pre-print
We present the first edition of "VIPriors: Visual Inductive Priors for Data-Efficient Deep Learning" challenges. We offer four data-impaired challenges, where models are trained from scratch, and we reduce the number of training samples to a fraction of the full set. Furthermore, to encourage data efficient solutions, we prohibited the use of pre-trained models and other transfer learning techniques. The majority of top ranking solutions make heavy use of data augmentation, model ensembling,
more » ... novel and efficient network architectures to achieve significant performance increases compared to the provided baselines.
arXiv:2103.03768v1 fatcat:6dyhmwh3unhkrifcrfk5dbphni