… In this work we extend 3D CNNs to significantly longer temporal convolutions that enable
action representation at their full temporal scale. We also explore the impact of optical flow input…

… convolution into a 2D spatial convolution followed by 1D temporal convolution, which we name
(2+1)D convolution… chitecture [13], (2+1)D convolutions lead to state-of-theart results on 4 …

… into separate components respectively for spatial and temporal convolutions. The … in the
action recognition literature, we introduce the concept of trajectory convolution. In trajectory …

… Video-based action recognition with deep neural networks has shown … action recognition
architecture, called Temporal Convolutional 3D Network (T-C3D), which learns video action …

… To learn spatial and temporal convolution kernels effectively, we follow the ideas from [28]
and … In Table 1, we also compare with [10] in the setting of using temporal convolution pipeline …

… with a 3D convolution. Therefore, we argue that spatio-temporal convolutions of video data
with … for the current availability of training data per action class. We observe that the motion in …

… of temporal models, which we call Temporal Convolutional Networks (TCNs), that use a
hierarchy of temporal convolutions to perform fine-grained action … long-range temporal patterns …

… , to capture the overall temporal dynamics from an entire video in a single process … action
recognition. It remains an open question for action recognition on how to deal with the temporal …

… in both temporal action proposal and temporal action localization task. Our results
suggested that anchor mechanisms and temporal convolution can work well in temporal action …

… spatialtemporal structure, we apply temporal convolution on the local spatial-temporal …
employs a separate channel-wise and temporal-wise convolution over the feature sequence of a …