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Learning Representations from Spatio-Temporal Distance Maps for 3D Action Recognition with Convolutional Neural Networks

https://doi.org/10.14201/adcai201982518

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-16811-1_35openalex-snapshot

Gesture Modeling by Hanklet-Based Hidden Markov Model

inferredcites →https://doi.org/10.1007/978-3-319-16817-3_27openalex-snapshot

Spectral Graph Skeletons for 3D Action Recognition

inferredcites →https://doi.org/10.1007/978-3-319-46487-9_50openalex-snapshot

Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

inferredcites →https://doi.org/10.1007/978-3-642-28661-2_5openalex-snapshot

Real-Time Human Pose Recognition in Parts from Single Depth Images

inferredcites →https://doi.org/10.1007/978-3-642-37798-3_15openalex-snapshot

Optimal Joint Selection for Skeletal Data from RGB-D Devices Using a Genetic Algorithm

inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot

ImageNet Large Scale Visual Recognition Challenge

inferredcites →https://doi.org/10.1016/j.imavis.2009.11.014openalex-snapshot

A survey on vision-based human action recognition

inferredcites →https://doi.org/10.1016/j.patcog.2015.11.019openalex-snapshot

3D skeleton-based human action classification: A survey

inferredcites →https://doi.org/10.1016/j.patcog.2017.10.033openalex-snapshot

Convolutional Neural Networks and Long Short-Term Memory for skeleton-based human activity and hand gesture recognition

inferredcites →https://doi.org/10.1016/j.patcog.2018.03.030openalex-snapshot

Learning content and style: Joint action recognition and person identification from human skeletons

inferredcites →https://doi.org/10.1016/s0893-6080(98)00116-6openalex-snapshot

On the momentum term in gradient descent learning algorithms

inferredcites →https://doi.org/10.1109/acpr.2015.7486569openalex-snapshot

Skeleton based action recognition with convolutional neural network

inferredcites →https://doi.org/10.1109/cvpr.2013.123openalex-snapshot

An Approach to Pose-Based Action Recognition

inferredcites →https://doi.org/10.1109/cvpr.2014.82openalex-snapshot

Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group

inferredcites →https://doi.org/10.1109/cvpr.2015.7298714openalex-snapshot

Hierarchical recurrent neural network for skeleton based action recognition

inferredcites →https://doi.org/10.1109/cvpr.2015.7298880openalex-snapshot

Hyper-class augmented and regularized deep learning for fine-grained image classification

inferredcites →https://doi.org/10.1109/cvpr.2015.7299100openalex-snapshot

Mirror, mirror on the wall, tell me, is the error small?

inferredcites →https://doi.org/10.1109/cvpr.2016.115openalex-snapshot

NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis

inferredcites →https://doi.org/10.1109/cvpr.2017.137openalex-snapshot

Deep Learning on Lie Groups for Skeleton-Based Action Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.387openalex-snapshot

Modeling Temporal Dynamics and Spatial Configurations of Actions Using Two-Stream Recurrent Neural Networks

inferredcites →https://doi.org/10.1109/cvpr.2017.391openalex-snapshot

Global Context-Aware Attention LSTM Networks for 3D Action Recognition

inferredcites →https://doi.org/10.1109/cvprw.2012.6239233openalex-snapshot

View invariant human action recognition using histograms of 3D joints

inferredcites →https://doi.org/10.1109/cvprw.2013.153openalex-snapshot

Bio-inspired Dynamic 3D Discriminative Skeletal Features for Human Action Recognition

inferredcites →https://doi.org/10.1109/cvprw.2013.76openalex-snapshot

Joint Angles Similarities and HOG2 for Action Recognition

inferredcites →https://doi.org/10.1109/dicta.2014.7008101openalex-snapshot

Discriminative Key Pose Extraction Using Extended LC-KSVD for Action Recognition

inferredcites →https://doi.org/10.1109/dicta.2014.7008115openalex-snapshot

Mining Mid-Level Features for Action Recognition Based on Effective Skeleton Representation

inferredcites →https://doi.org/10.1109/iccv.2015.164openalex-snapshot

Holistically-Nested Edge Detection

inferredcites →https://doi.org/10.1109/iccv.2015.290openalex-snapshot

Augmenting Strong Supervision Using Web Data for Fine-Grained Categorization

inferredcites →https://doi.org/10.1109/iccv.2017.115openalex-snapshot

Ensemble Deep Learning for Skeleton-Based Action Recognition Using Temporal Sliding LSTM Networks

inferredcites →https://doi.org/10.1109/icip.2015.7350781openalex-snapshot

UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor

inferredcites →https://doi.org/10.1109/icmew.2017.8026286openalex-snapshot

Investigation of different skeleton features for CNN-based 3D action recognition

inferredcites →https://doi.org/10.1109/icpr.2014.772openalex-snapshot

Skeletal Quads: Human Action Recognition Using Joint Quadruples

inferredcites →https://doi.org/10.1109/tassp.1981.1163711openalex-snapshot

Cubic convolution interpolation for digital image processing

inferredcites →https://doi.org/10.1109/wacv.2017.24openalex-snapshot

On Geometric Features for Skeleton-Based Action Recognition Using Multilayer LSTM Networks

inferredcites →https://doi.org/10.1145/1073204.1073247openalex-snapshot

Efficient content-based retrieval of motion capture data

inferredcites →https://doi.org/10.1145/2964284.2967191openalex-snapshot

Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks

inferredcites →https://doi.org/10.1145/3065386openalex-snapshot

ImageNet classification with deep convolutional neural networks

inferredcites →https://doi.org/10.1609/aaai.v31i1.11212openalex-snapshot

An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data

inferredcites →https://doi.org/10.48550/arxiv.1207.0580openalex-snapshot

Improving neural networks by preventing co-adaptation of feature detectors

inferredcites →https://doi.org/10.48550/arxiv.1412.0233openalex-snapshot

The Loss Surfaces of Multilayer Networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4191360openalex-extracted

inferred← citeshttps://doi.org/10.1007/s00500-023-07862-1openalex-snapshot

Direction-guided two-stream convolutional neural networks for skeleton-based action recognition

inferred← citeshttps://doi.org/10.1016/j.jvcir.2023.103781openalex-snapshot

A Convolutional Autoencoder Model with Weighted Multi-Scale Attention Modules for 3d Skeleton-Based Action Recognition

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