Active Generation for Image Classification

arXiv:2403.06517v1 Announce Type: new
Abstract: Recently, the growing capabilities of deep generative models have underscored their potential in enhancing image classification accuracy. However, existing methods often demand the generation of a disproportionately large number of images compared to the original dataset, while having only marginal improvements in accuracy. This computationally expensive and time-consuming process hampers the practicality of such approaches. In this paper, we propose to address the efficiency of image generation by focusing on the specific needs and characteristics …

abstract accuracy arxiv capabilities classification cs.ai cs.cv dataset deep generative models demand generative generative models however image images improvements process type