Your Image is My Video: Reshaping the Receptive Field via Image-To-Video Differentiable AutoAugmentation and Fusion

arXiv:2403.15194v1 Announce Type: cross
Abstract: The landscape of deep learning research is moving towards innovative strategies to harness the true potential of data. Traditionally, emphasis has been on scaling model architectures, resulting in large and complex neural networks, which can be difficult to train with limited computational resources. However, independently of the model size, data quality (i.e. amount and variability) is still a major factor that affects model generalization. In this work, we propose a novel technique to exploit available …

abstract architectures arxiv cs.cv cs.lg data deep learning differentiable fusion harness image image-to-video landscape moving networks neural networks research scaling strategies train true type via video