Learning to Generate Posters of Scientific Papers by Probabilistic Graphical Models
- 4 Downloads
Researchers often summarize their work in the form of scientific posters. Posters provide a coherent and efficient way to convey core ideas expressed in scientific papers. Generating a good scientific poster, however, is a complex and time-consuming cognitive task, since such posters need to be readable, informative, and visually aesthetic. In this paper, for the first time, we study the challenging problem of learning to generate posters from scientific papers. To this end, a data-driven framework, which utilizes graphical models, is proposed. Specifically, given content to display, the key elements of a good poster, including attributes of each panel and arrangements of graphical elements, are learned and inferred from data. During the inference stage, the maximum a posterior (MAP) estimation framework is employed to incorporate some design principles. In order to bridge the gap between panel attributes and the composition within each panel, we also propose a recursive page splitting algorithm to generate the panel layout for a poster. To learn and validate our model, we collect and release a new benchmark dataset, called NJU-Fudan Paper-Poster dataset, which consists of scientific papers and corresponding posters with exhaustively labelled panels and attributes. Qualitative and quantitative results indicate the effectiveness of our approach.
Keywordsgraphical design layout automation probabilistic graphical model
Unable to display preview. Download preview PDF.
- Jahanian A, Liu J, Tretter D R, Lin Q, Damera-Venkata N, O’Brien-Strain E, Lee S, Fan J, Allebach J P. Automatic design of magazine covers. In Proc. IS&T/SPIE Electronic Imaging, International Society for Optics and Photonics, January 2012, Article ID. 83020.Google Scholar
- Hunter A, Slatter D, Greig D. Web-based magazine design for self publishers. In Proc. IS&T/SPIE Electronic Imaging, International Society for Optics and Photonics, January 2011, Article ID. 787902.Google Scholar
- Yu L F, Yeung S K, Tang C K, Terzopoulos D, Chan T F, Osher S J. Make it home: Automatic optimization of furniture arrangement. ACM Transactions on Graphics, 2011, 30(4): Article No. 86.Google Scholar
- Merrell P, Schkufza E, Li Z, Agrawala M, Koltun V. Interactive furniture layout using interior design guidelines. ACM Transactions on Graphics, 2011, 30(4): Article No. 87.Google Scholar
- Cao Y, Lau R W, Chan A B. Look over here: Attentiondirecting composition of manga elements. ACM Transactions on Graphics, 2014, 33(4): Article No. 94.Google Scholar
- Hurst N, Li W, Marriott K. Review of automatic document formatting. In Proc. the 9th ACM Symposium on Document Engineering, September 2009, pp.99-108.Google Scholar
- Damera-Venkata N, Bento J, O’Brien-Strain E. Probabilistic document model for automated document composition. In Proc. the 11th ACM Symposium on Document Engineering, September 2011, pp.3-12.Google Scholar
- Mihalcea R, Tarau P. TextRank: Bringing order into text. In Proc. the 2004 Conference on Empirical Methods in Natural Language Processing, July 2004, pp.404-411.Google Scholar
- Qiang Y T, Fu Y W, Zhou Y W, Zhou Z H, Sigal L. Learning to generate posters of scientific papers. In Proc. the 30th AAAI Conference on Artificial Intelligence, February 2016, pp.51-57.Google Scholar
- Holland J H. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence. A Bradford Book, 1992.Google Scholar
- Goldberg D E. Genetic Algorithms in Search, Optimization and Machine Learning (1st edition). Addison Wesley, 1989.Google Scholar
- Gajos K, Weld D S. Preference elicitation for interface optimization. In Proc. the 18th Annual ACM Symposium on User Interface Software and Technology, October 2005, pp.173-182.Google Scholar
- Sarrafzadeh M, Lee D T. Algorithmic Aspects of VLSI Layout. World Scientific Pub. Co. Inc., 1993.Google Scholar
- Battista G D, Eades P, Tamassia R, Tollis I G. Graph Drawing: Algorithms for the Visualization of Graphs (1st edition). Pearson, 1998.Google Scholar
- Matsui Y, Yamasaki T, Aizawa K. Interactive manga retargeting. In Proc. ACM SIGGRAPH 2011 Posters, August 2011, Article No. 35.Google Scholar
- Hoashi K, Ono C, Ishii D, Watanabe H. Automatic preview generation of comic episodes for digitized comic search. In Proc. the 19th ACM International Conference on Multimedia, November 2011, pp.1489-1492.Google Scholar
- Qu Y, Pang W M, Wong T T, Heng P N. Richnesspreserving manga screening. ACM Transactions on Graphics, 2008, 27(5): Article No. 155.Google Scholar
- Arai K, Herman T. Method for automatic e-comic scene frame extraction for reading comic on mobile devices. In Proc. the 7th International Conference on Information Technology: New Generations, April 2010, pp.370-375.Google Scholar
- Pang X, Cao Y, Lau R W H, Chan A B. A robust panel extraction method for manga. In Proc. the 22nd ACM International Conference on Multimedia, November 2014, pp.1125-1128.Google Scholar
- Cao Y, Chan A B, Lau R W H. Automatic stylistic manga layout. ACM Transactions on Graphics, 2012, 31(6): Article No. 141.Google Scholar
- Kaser O, Lemire D. Tag-cloud drawing: Algorithms for cloud visualization. arXiv:0703109, 2007. https://arxiv.org/abs/cs/0703109, August 2018.
- Lok S, Feiner S. A survey of automated layout techniques for information presentations. In Proc. the 1st International Symposium on Smart Graphics, March 2001, pp.61-68.Google Scholar
- Harrington S J, Naveda J F, Jones R P, Roetling P, Thakkar N. Aesthetic measures for automated document layout. In Proc. the 2004 ACM Symposium on Document Engineering, October 2004, pp.109-111.Google Scholar
- Purvis L, Harrington S, O’Sullivan B, Freuder E C. Creating personalized documents: An optimization approach. In Proc. the 2003 ACM Symposium on Document Engineering, Nov. 2003, pp.68-77.Google Scholar
- Murphy K. The bayes net toolbox for Matlab. Technical Report, Computing Science and Statistics, 2001, http://people.cs.ubc.ca/~/Papers/bnt.pdf, Nov. 2018.
- Zhao Y, Zhu S C. Image parsing with stochastic scene grammar. In Proc. the 25th International Conference on Neural Information Processing Systems, December 2011, pp.73-81.Google Scholar
- Chen Z, Mukherjee A, Liu B, Hsu M, Castellanos M, Ghosh R. Leveraging multi-domain prior knowledge in topic models. In Proc. the 23rd International Joint Conference on Artificial Intelligence, August 2013, pp.2071-2077.Google Scholar