You Only Cut Once: Boosting Data Augmentation with a Single Cut. (arXiv:2201.12078v1 [cs.CV])

Web: http://arxiv.org/abs/2201.12078

We present You Only Cut Once (YOCO) for performing data augmentations. YOCO
cuts one image into two pieces and performs data augmentations individually
within each piece. Applying YOCO improves the diversity of the augmentation per
sample and encourages neural networks to recognize objects from partial
information. YOCO enjoys the properties of parameter-free, easy usage, and
boosting almost all augmentations for free. Thorough experiments are conducted
to evaluate its effectiveness. We first demonstrate that YOCO can be seamlessly
applied to varying …

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