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Existing single image reflection removal (SIRR) methods using deep learning tend to miss key low-frequency (LF) and high-frequency (HF) differences in images, affecting their effectiveness in removing reflections.
Separation of transparent layers using focus
Schechner, Y. Y., Kiryati, N., and Basri, R · 2000
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Separating reflections from a single image using local features
Levin, A., Zomet, A., and Weiss, Y · 2004
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Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., and Simoncelli, E. P · 2004
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User assisted separation of reflections from a single image using a sparsity prior
Levin, A. and Weiss, Y · 2007
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Scope of validity of psnr in image/video quality assessment
Huynh-Thu, Q. and Ghanbari, M · 2008
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Interference reflection separation from a single image
Chung, Y.-C., Chang, S.-L., Wang, J.-M., and Chen, S.-W · 2009
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The pascal visual object classes (voc) challenge
Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., and Zisserman, A · 2010
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Reflection removal using ghosting cues
Shih, Y., Krishnan, D., Durand, F., and Freeman, W. T · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., and Ganguli, S · 2015
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Depth of field guided reflection removal
Wan, R., Shi, B., Hwee, T. A., and Kot, A. C · 2016
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A generic deep architecture for single image reflection removal and image smoothing
Fan, Q., Yang, J., Hua, G., Chen, B., and Wipf, D · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
Huang, X. and Belongie, S · 2017
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Enhancenet: Single image super-resolution through automated texture synthesis
Sajjadi, M. S. M., Schölkopf, B., and Hirsch, M · 2017
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Benchmarking single-image reflection removal algorithms
Wan, R., Shi, B., Duan, L.-Y., Tan, A.-H., and Kot, A. C · 2017
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Multi-level wavelet-cnn for image restoration
Liu, P., Zhang, H., Zhang, K., Lin, L., and Zuo, W · 2018
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Region-aware reflection removal with unified content and gradient priors
Wan, R., Shi, B., Duan, L.-Y., Tan, A.-H., Gao, W., and Kot, A. C · 2018
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Seeing deeply and bidirectionally: A deep learning approach for single image reflection removal
Yang, J., Gong, D., Liu, L., and Shi, Q · 2018
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Single image reflection separation with perceptual losses
Zhang, X., Ng, R., and Chen, Q · 2018
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Single image reflection removal exploiting misaligned training data and network enhancements
Wei, K., Yang, J., Fu, Y., Wipf, D., and Huang, H · 2019
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Single image reflection removal beyond linearity
Wen, Q., Tan, Y., Qin, J., Liu, W., Han, G., and He, S · 2019
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Fast single image reflection suppression via convex optimization
Yang, Y., Ma, W., Zheng, Y., Cai, J.-F., and Xu, W · 2019
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Language models are few-shot learners
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al · 2020
Visual prompt tuning
Jia, M., Tang, L., Chen, B.-C., Cardie, C., Belongie, S., Hariharan, B., and Lim, S.-N · 2022
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Srdiff: Single image super-resolution with diffusion probabilistic models
Li, H., Yang, Y., Chang, M., Chen, S., Feng, H., Xu, Z., Li, Q., and Chen, Y · 2022
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Repaint: Inpainting using denoising diffusion probabilistic models
Lugmayr, A., Danelljan, M., Romero, A., Yu, F., Timofte, R., and Van Gool, L · 2022
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High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
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Palette: Image-to-image diffusion models
Saharia, C., Chan, W., Chang, H., Lee, C., Ho, J., Salimans, T., Fleet, D., and Norouzi, M · 2022
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Hairclip: Design your hair by text and reference image
Wei, T., Chen, D., Zhou, W., Liao, J., Tan, Z., Yuan, L., Zhang, W., and Yu, N · 2022
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Cited alongside, same era.
Single image reflection removal with physically-based training images
Kim, S., Huo, Y., and Yoon, S.-E · 2020
Cited alongside, same era.
Single image reflection removal through cascaded refinement
Li, C., Yang, Y., He, K., Lin, S., and Hopcroft, J. E · 2020
Cited alongside, same era.
Single image reflection removal with edge guidance, reflection classifier, and recurrent decomposition
Chang, Y.-C., Lu, C.-N., Cheng, C.-C., and Chiu, W.-C · 2021
Cited alongside, same era.
Diffusion models beat GANs on image synthesis
Dhariwal, P. and Nichol, A. Q · 2021
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Trash or treasure? an interactive dual-stream strategy for single image reflection separation
Hu, Q. and Guo, X · 2021
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Selective wavelet attention learning for single image deraining
Huang, H., Yu, A., Chai, Z., He, R., and Tan, T · 2021
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Restormer: Efficient transformer for high-resolution image restoration
Zamir, S. W., Arora, A., Khan, S., Hayat, M., Khan, F. S., and Yang, M.-H · 2022
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Learning to prompt for vision-language models
Zhou, K., Yang, J., Loy, C. C., and Liu, Z · 2022
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Decorate the newcomers: Visual domain prompt for continual test time adaptation
Gan, Y., Bai, Y., Lou, Y., Ma, X., Zhang, R., Shi, N., and Luo, L · 2023
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Maple: Multi-modal prompt learning
Khattak, M. U., Rasheed, H., Maaz, M., Khan, S., and Khan, F. S · 2023
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Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., and Neubig, G · 2023
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Image super-resolution via iterative refinement
Saharia, C., Ho, J., Chan, W., Salimans, T., Fleet, D. J., and Norouzi, M · 2023
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Robust single image reflection removal against adversarial attacks
Song, Z., Zhang, Z., Zhang, K., Luo, W., Fan, Z., Ren, W., and Lu, J · 2023
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Diffir: Efficient diffusion model for image restoration
Xia, B., Zhang, Y., Wang, S., Wang, Y., Wu, X., Tian, Y., Yang, W., and Van Gool, L · 2023
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Zhou, Y., Huang, J., Wang, C., Song, L., and Yang, G · 2023
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