Opto-Electronic Engineering, Volume. 49, Issue 6, 210423(2022)
A generative method for atmospheric polarization modelling based on neighborhood constraint
[7] [7] Quan W, Li J L, Gong X L, et al. INS/CNS/GNSS Integrated Navigation Technology[M]. Heidelberg: Springer, 2015.
[19] [19] Pathak D, Krhenbühl P, Donahue J, et al. Context encoders: feature learning by inpainting[C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016: 2536–2544.
[20] [20] Radford A, Metz L, Chintala S. Unsupervised representation learning with deep convolutional generative adversarial networks[C]//4th International Conference on Learning Representations, 2016.
[22] [22] Yan Z Y, Li X M, Li M, et al. Shift-Net: Image inpainting via deep feature rearrangement[C]//Proceedings of the 15th European Conference on Computer Vision (ECCV), 2018: 3–19.
[23] [23] Yu J H, Lin Z, Yang J M, et al. Generative image inpainting with contextual attention[C]//Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018: 5505–5514.
[24] [24] Liu G L, Reda F A, Shih K J, et al. Image inpainting for irregular holes using partial convolutions[C]//Proceedings of the 15th European Conference on Computer Vision (ECCV), 2018: 89–105.
[25] [25] Yu J H, Lin Z, Yang J M, et al. Free-form image inpainting with gated convolution[C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision, 2019: 4470–4479.
[26] [26] Xiong W, Yu J H, Lin Z, et al. Foreground-aware image inpainting[C]//Proceedings of 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019: 5833–5841.
[27] [27] Nazeri K, Ng E, Joseph T, et al. EdgeConnect: Structure guided image inpainting using edge prediction[C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019: 3265–3274.
[28] [28] Li J Y, He F X, Zhang L F, et al. Progressive reconstruction of visual structure for image inpainting[C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision, 2019: 5961–5970.
[29] [29] Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation[C]//Proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, 2015: 234–241.
[30] [30] Li J Y, Wang N, Zhang L F, et al. Recurrent feature reasoning for image inpainting[C]//Proceedings of 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020: 7757–7765.
[31] [31] Dang T Y, Liu Y T, Gao X J, et al. Multi-scale spatial transform network for atmospheric polarization prediction[C]//Proceedings of the 11thInternational Conference on Image and Graphics, 2021: 479–490.
Get Citation
Copy Citation Text
Qian Cheng, Xinjian Gao, Jun Gao, Xin Wang, Tianyi Dang, Yuan Yan. A generative method for atmospheric polarization modelling based on neighborhood constraint[J]. Opto-Electronic Engineering, 2022, 49(6): 210423
Category:
Received: Jan. 4, 2022
Accepted: --
Published Online: Jul. 7, 2022
The Author Email: Xinjian Gao (gaoxinjian@hfut.edu.cn)