114 citations · 277 across the 10 of their papers we have counts for
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cs.CV2017★ 114 cited
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh
The purpose of this study is to determine whether current video datasets have sufficient data for training very deep convolutional neural networks (CNNs) with spatio-temporal three…
cs.CV2017★ 79 cited
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…