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Image restoration is an important and challenging task in computer vision.Reverting a filtered image to its original image is helpful in various computervision tasks. We employ a nonlinear activation function free network (NAFNet)for a fast and lightweight model and add a color attention module that extractsuseful color information for better accuracy. We propose an accurate, fast,lightweight network with multi-scale and color attention for Instagram filterremoval (CAIR). Experiment results show that the proposed CAIR outperformsexisting Instagram filter removal networks in fast and lightweight ways, about11$\times$ faster and 2.4$\times$ lighter while exceeding 3.69 dB PSNR on IFFIdataset. CAIR can successfully remove the Instagram filter with high qualityand restore color information in qualitative results. The source code andpretrained weights are available at \url{https://github.com/HnV-Lab/CAIR}.

CAIR: Fast and Lightweight Multi-Scale Color Attention Network for Instagram Filter Removal