Generative Model Perception Rectification Algorithm for Trade-Off between Diversity and Quality
Guipeng Lan,
Shuai Xiao,
Jiachen Yang
et al.
Abstract:How to balance the diversity and quality of results from generative models through perception rectification poses a significant challenge. Abnormal perception in generative models is typically caused by two factors: inadequate model structure and imbalanced data distribution. In response to this issue, we propose the dynamic model perception rectification algorithm (DMPRA) for generalized generative models. The core idea is to gain a comprehensive perception of the data in the generative model by appropriately… Show more
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