Light Field Image Super-Resolution via Global-View Information Adaption and Angular Attention Fusion
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8145-8_21
Reference23 articles.
1. Zhu, H., Wang, Q., Yu, J.: Occlusion-model guided antiocclusion depth estimation in light field. IEEE J. Sel. Topics Signal Process. 11(7), 965–978 (2017)
2. Zhang, M., et al.: Memory-oriented decoder for light field salient object detection. In: NeurIPS 2019, pp. 896–906 (2019)
3. Zhang, S., Lin, Y., Sheng, H.: Residual networks for light field image super-resolution. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 11046–11055 (2019)
4. Jin, J., Hou, J., Chen, J., Kwong, S.: Light field spatial super-resolution via deep combinatorial geometry embedding and structural consistency regularization. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 2260–2269 (2020)
5. Y. Wang, L. Wang, J. Yang, W. An, J. Yu, Y. Guo, Spatial-angular interaction for light field image super-resolution, in: European Conference on Computer Vision, Springer, 2020, pp. 290–308
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