4 citations · 6 across the 4 of their papers we have counts for
4 papers
Action Recognition with Deep Multiple Aggregation Networks
Ahmed Mazari, Hichem Sahbi
Most of the current action recognition algorithms are based on deep networks which stack multiple convolutional, pooling and fully connected layers. While convolutional and fully c…
Deep hierarchical pooling design for cross-granularity action recognition
Ahmed Mazari, Hichem Sahbi
In this paper, we introduce a novel hierarchical aggregation design that captures different levels of temporal granularity in action recognition. Our design principle is coarse-to-…
Human Action Recognition with Multi-Laplacian Graph Convolutional Networks
Ahmed Mazari, Hichem Sahbi
Convolutional neural networks are nowadays witnessing a major success in different pattern recognition problems. These learning models were basically designed to handle vectorial d…
Human Action Recognition with Deep Temporal Pyramids
Ahmed Mazari, Hichem Sahbi
Deep convolutional neural networks (CNNs) are nowadays achieving significant leaps in different pattern recognition tasks including action recognition. Current CNNs are increasingl…