Learning to Generate Posters of Scientific PapersThis work is supported by NSFC (61333014, 61373059, and 61321491) and JiangsuSF (BK20150016).
Table 2: User study of different posters generated.
['Metric', 'Readability', 'Informativeness', 'Aesthetics', 'Avg.']
As in Tab. This validates the effectiveness of our method, since the inferred panel attributes and generated panel layout will save most valuable and important information. In contrast, our method is lower than the original posters on aesthetics metric (yet, still higher than those from novices). This is reasonable, since aesthetics is a relatively subjective metric and aesthetics generally requires a “human touch”. It is an open problem to generate more aesthetic posters from papers. Alignment.