Product2IMG: Prompt-Free E-commerce Product Background Generation with Diffusion Model and Self-Improved LMM

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.

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Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1145/3664647.3680753
Citations
3
Primary Topic
Video Analysis and Summarization
Type
article
Field-Weighted Citation Impact
0.75
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article

Product2IMG: Prompt-Free E-commerce Product Background Generation with Diffusion Model and Self-Improved LMM

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3 citations
Video Analysis and Summarization
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article

Product2IMG: Prompt-Free E-commerce Product Background Generation with Diffusion Model and Self-Improved LMM

Jiandong Zhang, Wenqing Yao, Jinhui Zhu, J Y Kong, Tingfeng Cao, Xue Zhao, Jin Fu Ding
article en
3 citations

Abstract

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.

Alibaba Group (China) (CN), South China University of Technology (CN)
Decent work and economic growth
Openalex Percentile: Top 27%
Video Analysis and Summarization
0.75
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