83 citations · 162 across the 3 of their papers we have counts for
3 papers
Retrieving and Highlighting Action with Spatiotemporal Reference
Seito Kasai, Yuchi Ishikawa, Masaki Hayashi +3
In this paper, we present a framework that jointly retrieves and spatiotemporally highlights actions in videos by enhancing current deep cross-modal retrieval methods. Our work tak…
Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?
Hirokatsu Kataoka, Tenga Wakamiya, Kensho Hara +1
How can we collect and use a video dataset to further improve spatiotemporal 3D Convolutional Neural Networks (3D CNNs)? In order to positively answer this open question in video r…
Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition
Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh
Convolutional neural networks with spatio-temporal 3D kernels (3D CNNs) have an ability to directly extract spatio-temporal features from videos for action recognition. Although th…