Speeded-up robust features (SURF), Comput. Vis. Image Underst, pp.346-359, 2008. ,
DOI : 10.1016/j.cviu.2007.09.014
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.738
POOF: Part-Based One-vs.-One Features for Fine-Grained Categorization, Face Verification, and Attribute Estimation, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013. ,
DOI : 10.1109/CVPR.2013.128
High Accuracy Optical Flow Estimation Based on a Theory for Warping, ECCV, 2004. ,
DOI : 10.1007/978-3-540-24673-2_3
The devil is in the details: an evaluation of recent feature encoding methods, Procedings of the British Machine Vision Conference 2011, 2011. ,
DOI : 10.5244/C.25.76
Return of the Devil in the Details: Delving Deep into Convolutional Nets, Proceedings of the British Machine Vision Conference 2014, 2014. ,
DOI : 10.5244/C.28.6
Articulated pose estimation by a graphical model with image dependent pairwise relations, NIPS, 2014. ,
Mixing Body-Part Sequences for Human Pose Estimation, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.302
URL : https://hal.archives-ouvertes.fr/hal-00978643
Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005. ,
DOI : 10.1109/CVPR.2005.177
URL : https://hal.archives-ouvertes.fr/inria-00548512
Human Detection Using Oriented Histograms of Flow and Appearance, ECCV, 2006. ,
DOI : 10.1023/A:1008162616689
URL : https://hal.archives-ouvertes.fr/inria-00548587
Imagenet: A large-scale hierarchical image database, CVPR, 2009. ,
Long-term recurrent convolutional networks for visual recognition and description, CVPR, 2015. ,
The Yael Library, Proceedings of the ACM International Conference on Multimedia, MM '14, 2014. ,
DOI : 10.1145/2647868.2654892
URL : https://hal.archives-ouvertes.fr/hal-01020695
Discovering localized attributes for fine-grained recognition, CVPR, 2012. ,
Two-Frame Motion Estimation Based on Polynomial Expansion, SCIA, 2003. ,
DOI : 10.1007/3-540-45103-X_50
Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography, Commun. ACM, 1981. ,
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.81
Finding action tubes, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. ,
DOI : 10.1109/CVPR.2015.7298676
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
ImageNet classification with deep convolutional neural networks, 2012. ,
HMDB: A large video database for human motion recognition, 2011 International Conference on Computer Vision, 2011. ,
DOI : 10.1109/ICCV.2011.6126543
Learning realistic human actions from movies, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008. ,
DOI : 10.1109/CVPR.2008.4587756
URL : https://hal.archives-ouvertes.fr/inria-00548659
Gradientbased learning applied to document recognition, Proceedings of the IEEE, 1998. ,
Multiple Granularity Analysis for Fine-Grained Action Detection, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.102
Action and Event Recognition with Fisher Vectors on a Compact Feature Set, 2013 IEEE International Conference on Computer Vision, 2013. ,
DOI : 10.1109/ICCV.2013.228
URL : https://hal.archives-ouvertes.fr/hal-00873662
Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.222
URL : https://hal.archives-ouvertes.fr/hal-00911179
Improving the Fisher Kernel for Large-Scale Image Classification, ECCV, 2010. ,
DOI : 10.1007/978-3-642-15561-1_11
URL : https://hal.archives-ouvertes.fr/inria-00548630
Poselet Conditioned Pictorial Structures, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013. ,
DOI : 10.1109/CVPR.2013.82
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.671.6521
A database for fine grained activity detection of cooking activities, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012. ,
DOI : 10.1109/CVPR.2012.6247801
Learning representations by back-propagating errors, Nature, vol.85, issue.6088, 1986. ,
DOI : 10.1038/323533a0
MODEC: Multimodal Decomposable Models for Human Pose Estimation, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013. ,
DOI : 10.1109/CVPR.2013.471
Parsing human motion with stretchable models, CVPR 2011, 2011. ,
DOI : 10.1109/CVPR.2011.5995607
Recognizing human actions: a local SVM approach, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., 2004. ,
DOI : 10.1109/ICPR.2004.1334462
Two-stream convolutional networks for action recognition in videos, NIPS, 2014. ,
UCF101: A dataset of 101 human actions classes from videos in the wild, CRCV-TR-12-01, 2012. ,
Deepface: Closing the gap to human-level performance in face verification, CVPR, 2014. ,
Joint training of a convolutional network and a graphical model for human pose estimation, NIPS, 2014. ,
DeepPose: Human Pose Estimation via Deep Neural Networks, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.214
URL : http://arxiv.org/abs/1312.4659
Action recognition by dense trajectories, CVPR 2011, 2011. ,
DOI : 10.1109/CVPR.2011.5995407
URL : https://hal.archives-ouvertes.fr/inria-00583818
Dense Trajectories and Motion Boundary Descriptors for Action Recognition, International Journal of Computer Vision, vol.73, issue.2, pp.60-79, 2013. ,
DOI : 10.1007/s11263-012-0594-8
URL : https://hal.archives-ouvertes.fr/hal-00725627
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
Articulated pose estimation with flexible mixtures-of-parts, CVPR 2011, 2011. ,
DOI : 10.1109/CVPR.2011.5995741
Beyond short snippets: Deep networks for video classification, CVPR, 2015. ,
Interaction part mining: A mid-level approach for fine-grained action recognition, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. ,
DOI : 10.1109/CVPR.2015.7298953
Pipelining Localized Semantic Features for Fine-Grained Action Recognition, ECCV, 2014. ,
DOI : 10.1007/978-3-319-10593-2_32