Boost image captioning with knowledge reasoning

Author:

Huang Feicheng,Li ZhixinORCID,Wei Haiyang,Zhang Canlong,Ma Huifang

Funder

National Natural Science Foundation of China

National Natural Science Foundatioin of China

Natural Science Foundation of Guangxi Province

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference48 articles.

1. Anderson, P., He, X., Buehler, C., Teney, D., Johnson, M., Gould, S., & Zhang, L. (2018). Bottom-up and top-down attention for image captioning and visual question answering. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 6077–6086).

2. Anne H. L., Venugopalan, S., Rohrbach, M., Mooney, R., Saenko, K., & Darrell, T. (2016). Deep compositional captioning: Describing novel object categories without paired training data. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1–10).

3. Bai, S., & An, S. (2018). A survey on automatic image caption generation. Neurocomputing, 311, 291–304.

4. Banerjee, S., & Lavie, A. (2005). Meteor: An automatic metric for mt evaluation with improved correlation with human judgments. In Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization (pp. 65–72).

5. Bengio, S., Vinyals, O., Jaitly, N., & Shazeer, N. (2015). Scheduled sampling for sequence prediction with recurrent neural networks. In Advances in neural information processing systems (pp. 1171–1179).

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