Learning Mid-Level Vision from Nothing but Data (Stella Yu, University of Michigan) скачать в хорошем качестве

Learning Mid-Level Vision from Nothing but Data (Stella Yu, University of Michigan)

ECCV 2022 CVinW Workshop Invited Talk: Learning Mid-Level Vision from Nothing but Data (Stella Yu, University of Michigan) Abstract: Computer vision with deep learning has achieved super-human performance on various benchmarks. However, deep neural network models are highly specialized for the task and the data they are trained on. In contrast, babies with normal vision eventually all learn to see from their widely different visual experiences. I attribute this fascinating development of universal visual perception to the ability of learning mid-level visual representations from data without any external supervision. I will present our recent work on unsupervised learning of visual recognition from unlabeled videos and images, demonstrating that structures in the visual data can be discovered from nothing but data with minimal priors and model bottlenecks.