On the use of deep learning for video classification
The video classification task has gained significant success in the recent years. Specifically,
the topic has gained more attention after the emergence of deep learning models as a …
the topic has gained more attention after the emergence of deep learning models as a …
Deep learning for video classification: A review
Video classification task has gained a significant success in the recent years. Specifically,
the topic has gained more attention after the emergence of deep learning models as a …
the topic has gained more attention after the emergence of deep learning models as a …
Channel Attention‐Based Approach with Autoencoder Network for Human Action Recognition in Low‐Resolution Frames
E Dastbaravardeh, S Askarpour… - … Journal of Intelligent …, 2024 - Wiley Online Library
Action recognition (AR) has many applications, including surveillance, health/disabilities
care, man‐machine interactions, video‐content‐based monitoring, and activity recognition …
care, man‐machine interactions, video‐content‐based monitoring, and activity recognition …
Spatio-temporal vector of locally max pooled features for action recognition in videos
We introduce Spatio-Temporal Vector of Locally Max Pooled Features (ST-VLMPF), a super
vector-based encoding method specifically designed for local deep features encoding. The …
vector-based encoding method specifically designed for local deep features encoding. The …
Linear dynamical systems approach for human action recognition with dual-stream deep features
Z Du, H Mukaidani - Applied Intelligence, 2022 - Springer
Human action recognition with a dual-stream architecture using linear dynamical systems
(LDSs) approach is discussed in this paper. First, a slice process is established to extract …
(LDSs) approach is discussed in this paper. First, a slice process is established to extract …
Two-branch relational prototypical network for weakly supervised temporal action localization
As a challenging task of high-level video understanding, weakly supervised temporal action
localization has attracted more attention recently. With only video-level category labels, this …
localization has attracted more attention recently. With only video-level category labels, this …
Spatio-temporal vlad encoding for human action recognition in videos
Encoding is one of the key factors for building an effective video representation. In the recent
works, super vector-based encoding approaches are highlighted as one of the most …
works, super vector-based encoding approaches are highlighted as one of the most …
Efficient human action recognition using histograms of motion gradients and VLAD with descriptor shape information
Feature extraction and encoding represent two of the most crucial steps in an action
recognition system. For building a powerful action recognition pipeline it is important that …
recognition system. For building a powerful action recognition pipeline it is important that …
Human action recognition based on spatio-temporal three-dimensional scattering transform descriptor and an improved VLAD feature encoding algorithm
The local spatio-temporal descriptor and feature encoding algorithm are two crucial key
steps for human action recognition based on spatio-temporal interest points (STIP). Since …
steps for human action recognition based on spatio-temporal interest points (STIP). Since …
Machine cognition of violence in videos using novel outlier-resistant vlad
Understanding highly accurate and real-time violent actions from surveillance videos is a
demanding challenge. Our primary contribution of this work is divided into two parts. Firstly …
demanding challenge. Our primary contribution of this work is divided into two parts. Firstly …