Cross-lingual methods can bring the benefits of genre classification to languages which lack genre-annotated training data. However, prior work in this field has been evaluated on coarse genres only. To predict fine-grained genres across languages, we propose a label propagation method, which combines separate sets of features. The results are promising, as the approach outperforms most baselines in our experiments.