Product2IMG: Prompt-Free E-commerce Product Background Generation with Diffusion Model and Self-Improved LMM
Tingfeng Cao, Junsheng Kong, Xue Zhao, Wenqing Yao, Junwei Ding, Jinhui Zhu, Jiandong Zhang · 2024
In e-commerce platforms, visual content plays a pivotal role in capturing and retaining audience attention. A high-quality and aesthetically designed product background image can quickly grab consumers' attention, and increase their confidence in taking actions, such as making a purchase. Recently, diffusion models have achieved profound advancements, rendering product background generation a promising avenue for exploration. However, text-guided diffusion models require meticulously crafted prompts. The diverse range of products makes it challenging to compose prompts that result in visually appealing and semantically appropriate background scenes. Current work has made great efforts on creating prompts through expert-crafted rules or specialized fine-tuning of large language models, but it still relies on detailed human inputs and often falls short in generating desirable results by e-commerce standards.