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Multi-weather image restoration has witnessed incredible progress, while the increasing model capacity and expensive data acquisition impair its applications in memory-limited devices.
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Learning deep CNN denoiser prior for image restoration
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Cycle-dehaze: Enhanced cyclegan for single image dehazing
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Progressive image deraining networks: A better and simpler baseline
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A Simple Framework for Contrastive Learning of Visual Representations
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An Unsupervised Attentive-Adversarial Learning Framework for Single Image Deraining
Liu, W.; Jiang, R.; Chen, C.; Lu, T.; and Xiong, Z. 2022 · 2022
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Cycle-snspgan: Towards real-world image dehazing via cycle spectral normalized soft likelihood estimation patch gan
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He, K.; Fan, H.; Wu, Y.; Xie, S.; and Girshick, R. 2020 · 2020
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Data-Efficient Image Recognition with Contrastive Predictive Coding
Hénaff, O. J. 2020 · 2020
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Denoising diffusion probabilistic models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
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Multi-scale progressive fusion network for single image deraining
Jiang, K.; Wang, Z.; Yi, P.; Chen, C.; Huang, B.; Luo, Y.; Ma, J.; and Jiang, J. 2020 · 2020
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Contrastive learning for unpaired image-to-image translation
Park, T.; Efros, A. A.; Zhang, R.; and Zhu, J.-Y. 2020 · 2020
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FFA-Net: Feature fusion attention network for single image dehazing
Qin, X.; Wang, Z.; Bai, Y.; Xie, X.; and Jia, H. 2020 · 2020
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Perceptual image quality assessment with transformers
Cheon, M.; Yoon, S.-J.; Kang, B.; and Lee, J. 2021 · 2021
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Self-augmented unpaired image dehazing via density and depth decomposition
Yang, Y.; Wang, C.; Liu, R.; Zhang, L.; Guo, X.; and Tao, D. 2022 · 2022
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Unsupervised deraining: Where contrastive learning meets self-similarity
Ye, Y.; Yu, C.; Chang, Y.; Zhu, L.; Zhao, X.-L.; Yan, L.; and Tian, Y. 2022 · 2022
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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 · 2022
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Spatext: Spatio-textual representation for controllable image generation
Avrahami, O.; Hayes, T.; Gafni, O.; Gupta, S.; Taigman, Y.; Parikh, D.; Lischinski, D.; Fried, O.; and Yin, X. 2023 · 2023
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Unsupervised deraining: Where asymmetric contrastive learning meets self-similarity
Chang, Y.; Guo, Y.; Ye, Y.; Yu, C.; Zhu, L.; Zhao, X.; Yan, L.; and Tian, Y. 2023 · 2023
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Cycle-attention-derain: unsupervised rain removal with CycleGAN
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Prompt tuning inversion for text-driven image editing using diffusion models
Dong, W.; Xue, S.; Duan, X.; and Han, S. 2023 · 2023
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Masked diffusion transformer is a strong image synthesizer
Gao, S.; Zhou, P.; Cheng, M.-M.; and Yan, S. 2023 · 2023
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Illumination controllable dehazing network based on unsupervised retinex embedding
Gui, J.; Cong, X.; He, L.; Tang, Y. Y.; and Kwok, J. T.-Y. 2023 · 2023
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USID-Net: Unsupervised Single Image Dehazing Network via Disentangled Representations
Li, J.; Li, Y.; Zhuo, L.; Kuang, L.; and Yu, T. 2023 · 2023
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Mou, C.; Wang, X.; Xie, L.; Wu, Y.; Zhang, J.; Qi, Z.; Shan, Y.; and Qie, X. 2023 · 2023
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Image desnowing via deep invertible separation
Quan, Y.; Tan, X.; Huang, Y.; Xu, Y.; and Ji, H. 2023 · 2023
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Vision transformers for single image dehazing
Song, Y.; He, Z.; Qian, H.; and Du, X. 2023 · 2023
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Distribution shift matters for knowledge distillation with webly collected images
Tang, J.; Chen, S.; Niu, G.; Sugiyama, M.; and Gong, C. 2023 · 2023
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Visual-quality-driven unsupervised image dehazing
Yang, A.; Liu, Y.; Wang, J.; Li, X.; Cao, J.; Ji, Z.; and Pang, Y. 2023 · 2023
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Zhang, L.; Rao, A.; and Agrawala, M. 2023 · 2023
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HCSD-Net: Single Image Desnowing with Color Space Transformation
Zhang, T.; Jiang, N.; Wu, H.; Zhang, K.; Niu, Y.; and Zhao, T. 2023 · 2023
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Rethinking Multi-Scale Representations in Deep Deraining Transformer
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Controlling Vision-Language Models for Multi-Task Image Restoration
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