Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey

16 Feb 2019Longlong JingYingli Tian

Large-scale labeled data are generally required to train deep neural networks in order to obtain better performance in visual feature learning from images or videos for computer vision applications. To avoid extensive cost of collecting and annotating large-scale datasets, as a subset of unsupervised learning methods, self-supervised learning methods are proposed to learn general image and video features from large-scale unlabeled data without using any human-annotated labels... (read more)

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