Dynamic image networks for action recognition, CVPR, 2016, p.8 ,
DOI : 10.1109/cvpr.2016.331
URL : https://pure.uva.nl/ws/files/19630210/cvpr2016bilen.pdf
High Accuracy Optical Flow Estimation Based on a Theory for Warping, ECCV, 2004. ,
DOI : 10.1007/978-3-540-24673-2_3
Action recognition with joints-pooled 3D deep convolutional descriptors, IJ- CAI, 2016. ,
Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008. ,
DOI : 10.1109/CVPR.2017.143
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008. ,
DOI : 10.1109/CVPR.2017.502
P-CNN: Pose-Based CNN Features for Action Recognition, 2015 IEEE International Conference on Computer Vision (ICCV), 2008. ,
DOI : 10.1109/ICCV.2015.368
Deep Temporal Linear Encoding Networks, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. ,
DOI : 10.1109/CVPR.2017.168
URL : http://arxiv.org/pdf/1611.06678
Long-term recurrent convolutional networks for visual recognition and description, CVPR, 2015. ,
RPAN: An End-to-End Recurrent Pose-Attention Network for Action Recognition in Videos, 2017 IEEE International Conference on Computer Vision (ICCV), 2017. ,
DOI : 10.1109/ICCV.2017.402
Hierarchical recurrent neural network for skeleton based action recognition, CVPR, 2015. ,
Spatiotemporal residual networks for video action recognition, NIPS, 2016, p.8 ,
Convolutional Two-Stream Network Fusion for Video Action Recognition, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), p.8 ,
DOI : 10.1109/CVPR.2016.213
Attentional pooling for action recognition, NIPS, 2008. ,
Finding action tubes, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008. ,
DOI : 10.1109/CVPR.2015.7298676
Understanding the difficulty of training deep feedforward neural networks, ICAIS, 2010. ,
Deep Residual Learning for Image Recognition, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. ,
DOI : 10.1109/CVPR.2016.90
Batch normalization: Accelerating deep network training by reducing internal covariate shift, ICML, 2015. ,
FusionSeg: Learning to Combine Motion and Appearance for Fully Automatic Segmentation of Generic Objects in Videos, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. ,
DOI : 10.1109/CVPR.2017.228
Towards Understanding Action Recognition, 2013 IEEE International Conference on Computer Vision, 2013. ,
DOI : 10.1109/ICCV.2013.396
URL : https://hal.archives-ouvertes.fr/hal-00906902
Action Tubelet Detector for Spatio-Temporal Action Localization, 2017 IEEE International Conference on Computer Vision (ICCV), 2017. ,
DOI : 10.1109/ICCV.2017.472
URL : https://hal.archives-ouvertes.fr/hal-01519812
Adam: A method for stochastic optimization, ICLR, 2015. ,
A Spatio-Temporal Descriptor Based on 3D-Gradients, Procedings of the British Machine Vision Conference 2008, 2008. ,
DOI : 10.5244/C.22.99
ImageNet classification with deep convolutional neural networks, NIPS, 2012. ,
DOI : 10.1162/neco.2009.10-08-881
URL : http://dl.acm.org/ft_gateway.cfm?id=3065386&type=pdf
HMDB: A large video database for human motion recognition, 2011 International Conference on Computer Vision, 2011. ,
DOI : 10.1109/ICCV.2011.6126543
On space-time interest points, IJCV, issue.1, 2005. ,
DOI : 10.1007/s11263-005-1838-7
URL : http://kth.diva-portal.org/smash/get/diva2:442088/FULLTEXT01
Microsoft COCO: Common Objects in Context, ECCV, 2014. ,
DOI : 10.1007/978-3-319-10602-1_48
Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition, ECCV, 2016. 1 ,
DOI : 10.1109/ISSNIP.2014.6827664
Stacked Hourglass Networks for Human Pose Estimation, ECCV, 2016. ,
DOI : 10.1109/ICCV.2015.178
URL : http://arxiv.org/pdf/1603.06937
Multi-region Two-Stream R-CNN for Action Detection, ECCV, 2008. ,
DOI : 10.1109/CVPR.2015.7298735
URL : https://hal.archives-ouvertes.fr/hal-01349107
Deep Learning for Detecting Multiple Space-Time Action Tubes in Videos, Procedings of the British Machine Vision Conference 2016, 2016. ,
DOI : 10.5244/C.30.58
NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) ,
DOI : 10.1109/CVPR.2016.115
Two-stream convolutional networks for action recognition in videos, NIPS, 2008. ,
Very deep convolutional networks for large-scale image recognition, ICLR, 2015. ,
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild, CRCV-TR-12-01, 2012. ,
Dropout: a simple way to prevent neural networks from overfitting, JMLR, issue.5, 2014. ,
Lattice Long Short-Term Memory for Human Action Recognition, 2017 IEEE International Conference on Computer Vision (ICCV), 2008. ,
DOI : 10.1109/ICCV.2017.236
Going deeper with convolutions, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. ,
DOI : 10.1109/CVPR.2015.7298594
Learning Motion Patterns in Videos, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. ,
DOI : 10.1109/CVPR.2017.64
URL : https://hal.archives-ouvertes.fr/hal-01427480
Learning Spatiotemporal Features with 3D Convolutional Networks, 2015 IEEE International Conference on Computer Vision (ICCV), 2008. ,
DOI : 10.1109/ICCV.2015.510
Convnet architecture search for spatiotemporal feature learning. arXiv, 2008. ,
An approach to posebased action recognition, CVPR, 2013. ,
Action Recognition with Improved Trajectories, 2013 IEEE International Conference on Computer Vision, 2013. ,
DOI : 10.1109/ICCV.2013.441
URL : https://hal.archives-ouvertes.fr/hal-00873267
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition, ECCV, 2008. ,
DOI : 10.1109/CVPR.2016.219
Joint action recognition and pose estimation from video, CVPR, 2015. ,
Beyond short snippets: Deep networks for video classification, CVPR, 2015. ,
A duality based approach for realtime TV-L1 optical flow. Pattern Recognition, 2007. ,
The Kinetics Human Action Video Dataset ,
Chained Multi-stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection, 2017 IEEE International Conference on Computer Vision (ICCV), 2008. ,
DOI : 10.1109/ICCV.2017.316