Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Skeleton-based action recognition with convolutional neural networks
Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates
Action recognition based on a mixture of RGB and depth based skeleton
Real-Time Multi-scale Action Detection from 3D Skeleton Data
Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group
Temporal Convolutional Networks for Action Segmentation and Detection
Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data
Do Less and Achieve More: Training CNNs for Action Recognition Utilizing Action Images from the Web
3D CNNs on Distance Matrices for Human Action Recognition
Dynamic Image Networks for Action Recognition
MoFAP: A Multi-level Representation for Action Recognition
Leveraging Hierarchical Parametric Networks for Skeletal Joints Based Action Segmentation and Recognition
Scene Flow to Action Map: A New Representation for RGB-D Based Action Recognition with Convolutional Neural Networks
A hierarchical representation for human action recognition in realistic scenes
sequential deep learning for human action recognition .
Differential Recurrent Neural Networks for Action Recognition
A Closer Look at Spatiotemporal Convolutions for Action Recognition
A BoW-equivalent Recurrent Neural Network for Action Recognition.
Moving Poselets: A Discriminative and Interpretable Skeletal Motion Representation for Action Recognition
Two-Stream Convolutional Networks for Action Recognition in Videos
Multi-criteria Shortest Paths in Time-Dependent Train Networks
SURREAL: Subgraph Robust Representation Learning
3D Convolutional Neural Networks for Human Action Recognition
The Wason Selection task: A Meta-Analysis.
Geographic Data Min-ing and Knowledge Discovery