Exploring Pairwise Spatial Relationships for Actions Recognition and Scene Graph Generation
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-34111-3_32
Reference40 articles.
1. Xu, D., Zhu, Y., Choy, C. B., Fei-Fei, L.: Scene graph generation by iterative message passing. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5410–5419 (2017)
2. Yin, G., et al.: Zoom-net: Mining deep feature interactions for visual relationship recognition. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 322–338 (2018)
3. Li, Y., Ouyang, W., Zhou, B., Wang, K., Wang, X.: Scene graph generation from objects, phrases and region captions. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1261–1270 (2017)
4. Li, S., Tang, M., Zhang, J., Jiang, L.: Attentive gated graph neural network for image scene graph generation. Symmetry 12(4), 511 (2020)
5. Tian, P., Mo, H., Jiang, L.: Exploring correlation of relationship reasoning for scene graph generation. Int. J. Mach. Learn. Cybern. 13(9), 2479–2493 (2022)
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