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A Probabilistic Semi-Supervised Approach to Multi-Task Human Activity Modeling
[article]
2019
arXiv
pre-print
Human behavior is a continuous stochastic spatio-temporal process which is governed by semantic actions and affordances as well as latent factors. Therefore, video-based human activity modeling is concerned with a number of tasks such as inferring current and future semantic labels, predicting future continuous observations as well as imagining possible future label and feature sequences. In this paper we present a semi-supervised probabilistic deep latent variable model that can represent both
arXiv:1809.08875v3
fatcat:dvgoa2kh2bcw7iet5xqugnc3ga