Adaptive Multi-granularity Aggregation Transformer for Image Captioning
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-50959-9_24
Reference24 articles.
1. Anderson, P., et al.: 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 (2018)
2. Cornia, M., Stefanini, M., Baraldi, L., Cucchiara, R.: Meshed-memory transformer for image captioning. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 10578–10587 (2020)
3. Fan, Z., et al.: TCIC: theme concepts learning cross language and vision for image captioning. arXiv preprint arXiv:2106.10936 (2021)
4. Fang, Z., et al.: Injecting semantic concepts into end-to-end image captioning. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 18009–18019 (2022)
5. Fei, Z.: Attention-aligned transformer for image captioning. In: proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, pp. 607–615 (2022)
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