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Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference
2019
2019 IEEE/CVF International Conference on Computer Vision (ICCV)
Deep neural networks (DNNs) provide state-of-the-art results for a multitude of applications, but the approaches using DNNs for multimodal audiovisual applications do not consider predictive uncertainty associated with individual modalities. Bayesian deep learning methods provide principled confidence and quantify predictive uncertainty. Our contribution in this work is to propose an uncertainty aware multimodal Bayesian fusion framework for activity recognition. We demonstrate a novel approach
doi:10.1109/iccv.2019.00640
dblp:conf/iccv/SubedarKLTH19
fatcat:pe7orp5eeff3tj4ltaij3ht4za