Swapping Semantic Contents for Mixing Images. (arXiv:2205.10158v1 [cs.CV])

Deep architecture have proven capable of solving many tasks provided a
sufficient amount of labeled data. In fact, the amount of available labeled
data has become the principal bottleneck in low label settings such as
Semi-Supervised Learning. Mixing Data Augmentations do not typically yield new
labeled samples, as indiscriminately mixing contents creates between-class
samples. In this work, we introduce the SciMix framework that can learn to
generator to embed a semantic style code into image backgrounds, we obtain new
mixing …

arxiv cv images semantic