ICCV 2019 Open Access Repository
These ICCV 2019 papers are the Open Access versions, provided by the Computer Vision Foundation. Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by ot
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RepPoints: Point Set Representation for Object Detection
GitHub - tamarott/SinGAN: Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
GitHub - albumentations-team/albumentations: Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks