Single-image driven 3d viewpoint training data augmentation for effective wine label recognition

arXiv:2404.08820v1 Announce Type: cross
Abstract: Confronting the critical challenge of insufficient training data in the field of complex image recognition, this paper introduces a novel 3D viewpoint augmentation technique specifically tailored for wine label recognition. This method enhances deep learning model performance by generating visually realistic training samples from a single real-world wine label image, overcoming the challenges posed by the intricate combinations of text and logos. Classical Generative Adversarial Network (GAN) methods fall short in synthesizing such intricate content …

abstract arxiv augmentation challenge cs.cv cs.lg data deep learning image image recognition novel paper performance recognition samples training training data type wine