Abstract
Ad creatives are ads served to users on a webpage, app, or other digital environments. The demand for compelling ad creatives surges drastically with the ever-increasing popularity of digital marketing. The two most essential elements of (display) ad creatives are the advertising message, such as headlines and description texts, and the visual component, such as images and videos. Traditionally, ad creatives are composed by professional copywriters and creative designers. The process requires significant human effort, limiting the scalability and efficiency of digital ad campaigns. This work introduces AUTOCREATIVE, a novel system to automatically generate ad creatives relying on natural language generation and computer vision techniques. The system generates multiple ad copies (ad headlines/description texts) using a sequence-to-sequence model and selects images most suitable to the generated ad copies based on heuristic-based visual appeal metrics and a text-image retrieval pipeline.- Anthology ID:
- 2022.inlg-demos.3
- Volume:
- Proceedings of the 15th International Conference on Natural Language Generation: System Demonstrations
- Month:
- July
- Year:
- 2022
- Address:
- Waterville, Maine, USA and virtual meeting
- Editors:
- Samira Shaikh, Thiago Ferreira, Amanda Stent
- Venue:
- INLG
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 7–9
- Language:
- URL:
- https://aclanthology.org/2022.inlg-demos.3
- DOI:
- Cite (ACL):
- Vishakha Kadam, Yiping Jin, and Bao-Dai Nguyen-Hoang. 2022. Automated Ad Creative Generation. In Proceedings of the 15th International Conference on Natural Language Generation: System Demonstrations, pages 7–9, Waterville, Maine, USA and virtual meeting. Association for Computational Linguistics.
- Cite (Informal):
- Automated Ad Creative Generation (Kadam et al., INLG 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2022.inlg-demos.3.pdf