Recipe Generation from a Photo Sequence by Focusing on Verbalizing Important Terms
Author:
Affiliation:
1. Graduate School of Informatics, Kyoto University
2. OMRON SINIC X Corporation
3. Academic Center for Computing and Media Studies, Kyoto University
Publisher
Association for Natural Language Processing
Link
https://www.jstage.jst.go.jp/article/jnlp/27/2/27_257/_pdf
Reference28 articles.
1. Balntas, V., Riba, E., Ponsa, D., and Mikolajczyk, K. (2016). “Learning Local Feature Descriptors with Triplets and Shallow Convolutional Neural Networks.” In Proceedings of the British Machine Vision Conference, pp. 1–11.
2. Biten, A. F., Gomez, L., Rusinol, M., and Karatzas, D. (2019). “Good News, Everyone! Context Driven Entity-Aware Captioning for News Images.” In Proceedings of the Conference on Computer Vision and Pattern Recognition, pp. 12466–12475.
3. Bosselut, A., Celikyilmaz, A., He, X., Gao, J., Huang, P.-S., and Choi, Y. (2018). “Discourse-Aware Neural Rewards for Coherent Text Generation.” In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 173–184.
4. Chandu, K., Nyberg, E., and Black, A. W. (2019). “Storyboarding of Recipes: Grounded Contextual Generation.” In Proceedings of the Annual Meeting of the Association for Computational Linguistics, pp. 6040–6046.
5. Chen, J. and Ngo, C.-W. (2016). “Deep-based Ingredient Recognition for Cooking Recipe Retrieval.” In Proceedings of the ACM International Conference on Multimedia, pp. 32–41.
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