The Learning and Vision Atelier (LAVA)

[CVPR 2019] Learning Parallax Attention for Stereo Image Super-Resolution

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[CVPR 2021] Exploring Sparsity in Image Super-Resolution for Efficient Inference

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[ICCV 2021] Learning A Single Network for Scale-Arbitrary Super-Resolution

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[CVPR 2021] Unsupervised Degradation Representation Learning for Blind Super-Resolution

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[ACCV 2018 & TIP 2020] Deep Video Super-resolution using HR Optical Flow Estimation

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A Collection of Algorithms and Datasets for Stereo Image Super-Resolution

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[TPAMI 2020] Parallax Attention for Unsupervised Stereo Correspondence Learning

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[CVPR 2022] Learnable Lookup Table for Neural Network Quantization

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[CVPR2022] Decoupling Makes Weakly Supervised Local Feature Better

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A Collection of Papers and Datasets for Light Field Image Super-Resolution

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