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Global operations, such as global average pooling, are widely used in top-performance image restorers.
Amir, A., Church, K.W., Dar, E.: The submatrices character count problem: an efficient solution using separable values. Information and Computation
2004
Earlier work this paper cites.
Harris, M., Sengupta, S., Owens, J.D.: Parallel prefix sum (scan) with cuda. GPU gems
2007
Earlier work this paper cites.
Lyu, S., Simoncelli, E.P.: Nonlinear image representation using divisive normalization. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition. pp. 1–8. IEEE (2008)
2008
Earlier work this paper cites.
Jarrett, K., Kavukcuoglu, K., Ranzato, M., LeCun, Y.: What is the best multi-stage architecture for object recognition? In: 2009 IEEE 12th international conference on computer vision. pp. 2146–2153. IEEE (2009)
2009
Earlier work this paper cites.
Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems
2012
Earlier work this paper cites.
Huang, J.B., Singh, A., Ahuja, N.: Single image super-resolution from transformed self-exemplars. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 5197–5206 (2015)
2015
Earlier work this paper cites.
Lee, N.Y.: Block-iterative richardson-lucy methods for image deblurring. EURASIP Journal on Image and Video Processing
2015
Earlier work this paper cites.
Shi, J., Xu, L., Jia, J.: Just noticeable defocus blur detection and estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 657–665 (2015)
2015
Earlier work this paper cites.
2016
Earlier work this paper cites.
Nah, S., Hyun Kim, T., Mu Lee, K.: Deep multi-scale convolutional neural network for dynamic scene deblurring. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 3883–3891 (2017)
2017
Earlier work this paper cites.
Zhang, K., Zuo, W., Chen, Y., Meng, D., Zhang, L.: Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising. IEEE transactions on image processing
2017
Earlier work this paper cites.
Zhang, K., Zuo, W., Gu, S., Zhang, L.: Learning deep cnn denoiser prior for image restoration. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 3929–3938 (2017)
2017
Earlier work this paper cites.
Hu, J., Shen, L., Albanie, S., Sun, G., Vedaldi, A.: Gather-excite: Exploiting feature context in convolutional neural networks. Advances in neural information processing systems
2018
Earlier work this paper cites.
Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 7132–7141 (2018)
2018
Earlier work this paper cites.
Li, B., Ren, W., Fu, D., Tao, D., Feng, D., Zeng, W., Wang, Z.: Benchmarking single-image dehazing and beyond. IEEE Transactions on Image Processing pp. 492–505 (2018)
2018
Earlier work this paper cites.
Li, X., Wu, J., Lin, Z., Liu, H., Zha, H.: Recurrent squeeze-and-excitation context aggregation net for single image deraining. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 254–269 (2018)
2018
Earlier work this paper cites.
Liu, D., Wen, B., Fan, Y., Loy, C.C., Huang, T.S.: Non-local recurrent network for image restoration. Advances in neural information processing systems
2018
Earlier work this paper cites.
Liu, P., Zhang, H., Zhang, K., Lin, L., Zuo, W.: Multi-level wavelet-cnn for image restoration. In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops. pp. 773–782 (2018)
2018
Earlier work this paper cites.
Woo, S., Park, J., Lee, J.Y., Kweon, I.S.: Cbam: Convolutional block attention module. In: Proceedings of the European conference on computer vision (ECCV). pp. 3–19 (2018)
2018
Earlier work this paper cites.
Wu, Y., He, K.: Group normalization. In: Proceedings of the European conference on computer vision (ECCV). pp. 3–19 (2018)
2018
Earlier work this paper cites.
Zhang, K., Zuo, W., Zhang, L.: Ffdnet: Toward a fast and flexible solution for cnn-based image denoising. IEEE Transactions on Image Processing
2018
Earlier work this paper cites.
Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 586–595 (2018)
2018
Earlier work this paper cites.
Zhang, Y., Li, K., Li, K., Wang, L., Zhong, B., Fu, Y.: Image super-resolution using very deep residual channel attention networks. In: Proceedings of the European conference on computer vision (ECCV). pp. 286–301 (2018)
2018
Earlier work this paper cites.
Anwar, S., Barnes, N.: Real image denoising with feature attention. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 3155–3164 (2019)
2019
Cited alongside, same era.
Gao, H., Tao, X., Shen, X., Jia, J.: Dynamic scene deblurring with parameter selective sharing and nested skip connections. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 3848–3856 (2019)
2019
Cited alongside, same era.
Lee, J., Lee, S., Cho, S., Lee, S.: Deep defocus map estimation using domain adaptation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 12222–12230 (2019)
2019
Cited alongside, same era.
Nah, S., Son, S., Lee, K.M.: Recurrent neural networks with intra-frame iterations for video deblurring. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 8102–8111 (2019)
2019
Cited alongside, same era.
Abuolaim, A., Delbracio, M., Kelly, D., Brown, M.S., Milanfar, P.: Learning to reduce defocus blur by realistically modeling dual-pixel data. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2289–2298 (2021)
2021
Closest in time.
Chen, H., Wang, Y., Guo, T., Xu, C., Deng, Y., Liu, Z., Ma, S., Xu, C., Xu, C., Gao, W.: Pre-trained image processing transformer. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 12299–12310 (2021)
2021
Closest in time.
Chen, L., Lu, X., Zhang, J., Chu, X., Chen, C.: Hinet: Half instance normalization network for image restoration. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (2021)
2021
Closest in time.
Cho, S.J., Ji, S.W., Hong, J.P., Jung, S.W., Ko, S.J.: Rethinking coarse-to-fine approach in single image deblurring. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 4641–4650 (2021)
2021
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Park, T., Liu, M.Y., Wang, T.C., Zhu, J.Y.: Semantic image synthesis with spatially-adaptive normalization. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2337–2346 (2019)
2019
Cited alongside, same era.
Shen, Z., Wang, W., Lu, X., Shen, J., Ling, H., Xu, T., Shao, L.: Human-aware motion deblurring. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 5572–5581 (2019)
2019
Cited alongside, same era.
Wang, T., Yang, X., Xu, K., Chen, S., Zhang, Q., Lau, R.W.: Spatial attentive single-image deraining with a high quality real rain dataset. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 12270–12279 (2019)
2019
Cited alongside, same era.
Wang, X., Chan, K.C., Yu, K., Dong, C., Change Loy, C.: Edvr: Video restoration with enhanced deformable convolutional networks. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (2019)
2019
Cited alongside, same era.
Zhang, H., Dai, Y., Li, H., Koniusz, P.: Deep stacked hierarchical multi-patch network for image deblurring. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 5978–5986 (2019)
2019
Cited alongside, same era.
2019
Cited alongside, same era.
Abuolaim, A., Brown, M.S.: Defocus deblurring using dual-pixel data. In: European Conference on Computer Vision. pp. 111–126. Springer (2020)
2020
Cited alongside, same era.
Pan, J., Bai, H., Tang, J.: Cascaded deep video deblurring using temporal sharpness prior. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 3043–3051 (2020)
2020
Cited alongside, same era.
Closest in time.
Lee, J., Son, H., Rim, J., Cho, S., Lee, S.: Iterative filter adaptive network for single image defocus deblurring. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2034–2042 (2021)
2021
Closest in time.
Liang, J., Cao, J., Sun, G., Zhang, K., Van Gool, L., Timofte, R.: Swinir: Image restoration using swin transformer. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 1833–1844 (2021)
2021
Closest in time.
Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., Guo, B.: Swin transformer: Hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 10012–10022 (2021)
2021
Closest in time.
Mou, C., Zhang, J., Wu, Z.: Dynamic attentive graph learning for image restoration. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 4328–4337 (2021)
2021
Closest in time.
Purohit, K., Suin, M., Rajagopalan, A., Boddeti, V.N.: Spatially-adaptive image restoration using distortion-guided networks. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2309–2319 (2021)
2021
Closest in time.
Ren, C., He, X., Wang, C., Zhao, Z.: Adaptive consistency prior based deep network for image denoising. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 8596–8606 (2021)
2021
Closest in time.
Son, H., Lee, J., Cho, S., Lee, S.: Single image defocus deblurring using kernel-sharing parallel atrous convolutions. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2642–2650 (2021)
2021
Closest in time.
Son, H., Lee, J., Lee, J., Cho, S., Lee, S.: Recurrent video deblurring with blur-invariant motion estimation and pixel volumes. ACM Transactions on Graphics (TOG)
2021
Closest in time.
Suin, M., Rajagopalan, A.: Gated spatio-temporal attention-guided video deblurring. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 7802–7811 (2021)
2021
Closest in time.
Yi, Q., Li, J., Dai, Q., Fang, F., Zhang, G., Zeng, T.: Structure-preserving deraining with residue channel prior guidance. In: IEEE International Conference on Computer Vision (2021)
2021
Closest in time.
Zamir, S.W., Arora, A., Khan, S., Hayat, M., Khan, F.S., Yang, M.H., Shao, L.: Multi-stage progressive image restoration. In: CVPR (2021)
2021
Closest in time.
Zamir, S.W., Arora, A., Khan, S., Hayat, M., Khan, F.S., Yang, M.H., Shao, L.: Multi-stage progressive image restoration. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 14821–14831 (2021)
2021
Closest in time.
Zhang, K., Li, Y., Zuo, W., Zhang, L., Van Gool, L., Timofte, R.: Plug-and-play image restoration with deep denoiser prior. IEEE Transactions on Pattern Analysis and Machine Intelligence (2021)
2021
Closest in time.
2022
Closest in time.
Chu, X., Chen, L., Yu, W.: Nafssr: Stereo image super-resolution using nafnet. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. pp. 1239–1248 (June 2022)
2022
Closest in time.
Wang, Z., Cun, X., Bao, J., Zhou, W., Liu, J., Li, H.: Uformer: A general u-shaped transformer for image restoration. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 17683–17693 (2022)
2022
Closest in time.
Zamir, S.W., Arora, A., Khan, S., Hayat, M., Khan, F.S., Yang, M.H.: Restormer: Efficient transformer for high-resolution image restoration. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 5728–5739 (2022)
2022
Closest in time.
Zhu, C., Dong, H., Pan, J., Liang, B., Huang, Y., Fu, L., Wang, F.: Deep recurrent neural network with multi-scale bi-directional propagation for video deblurring. In: Proceedings of the AAAI Conference on Artificial Intelligence. pp. 3598–3607 (2022)
2022
Closest in time.