On the Integration of Optical Flow and Action Recognition
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Michael J. Black | Varun Jampani | Yiyi Liao | Laura Sevilla-Lara | Andreas Geiger | Fatma Güney | Andreas Geiger | V. Jampani | Laura Sevilla-Lara | Yiyi Liao | F. Güney
[1] David J. Fleet,et al. Performance of optical flow techniques , 1994, International Journal of Computer Vision.
[2] Richard P. Wildes,et al. Spatiotemporal Multiplier Networks for Video Action Recognition , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[4] Richard P. Wildes,et al. Spatiotemporal Residual Networks for Video Action Recognition , 2016, NIPS.
[5] Michael J. Black,et al. Efficient sparse-to-dense optical flow estimation using a learned basis and layers , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Lorenzo Torresani,et al. Learning Spatiotemporal Features with 3D Convolutional Networks , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[7] Jonghyun Choi,et al. ActionFlowNet: Learning Motion Representation for Action Recognition , 2016, 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).
[8] Abhinav Gupta,et al. ActionVLAD: Learning Spatio-Temporal Aggregation for Action Classification , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Cordelia Schmid,et al. EpicFlow: Edge-preserving interpolation of correspondences for optical flow , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Mubarak Shah,et al. UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild , 2012, ArXiv.
[11] Ali Farhadi,et al. Asynchronous Temporal Fields for Action Recognition , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Thomas Brox,et al. FlowNet: Learning Optical Flow with Convolutional Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[13] Fei-Fei Li,et al. Large-Scale Video Classification with Convolutional Neural Networks , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[14] James W. Davis,et al. An appearance-based representation of action , 1996, Proceedings of 13th International Conference on Pattern Recognition.
[15] Thomas Brox,et al. FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Michael J. Black,et al. Optical Flow Estimation Using a Spatial Pyramid Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[18] Michael J. Black,et al. Learning Optical Flow , 2008, ECCV.
[19] Cordelia Schmid,et al. Long-Term Temporal Convolutions for Action Recognition , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[20] Luc Van Gool,et al. Temporal Segment Networks: Towards Good Practices for Deep Action Recognition , 2016, ECCV.
[21] P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .
[22] Fei-Fei Li,et al. Grouplet: A structured image representation for recognizing human and object interactions , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[23] Ross B. Girshick,et al. Mask R-CNN , 2017, 1703.06870.
[24] Тараса Шевченка,et al. Quo vadis? , 2013, Clinical chemistry.
[25] Michael J. Black,et al. On the Spatial Statistics of Optical Flow , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[26] Andrew Zisserman,et al. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Michael J. Black,et al. A Naturalistic Open Source Movie for Optical Flow Evaluation , 2012, ECCV.
[28] G. Johansson. Visual perception of biological motion and a model for its analysis , 1973 .
[29] Didier Stricker,et al. Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[30] Andrew Zisserman,et al. Convolutional Two-Stream Network Fusion for Video Action Recognition , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[31] Andreas Geiger,et al. Object scene flow for autonomous vehicles , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Thomas Serre,et al. HMDB: A large video database for human motion recognition , 2011, 2011 International Conference on Computer Vision.
[33] Cordelia Schmid,et al. Towards Understanding Action Recognition , 2013, 2013 IEEE International Conference on Computer Vision.
[34] Andrew Zisserman,et al. Two-Stream Convolutional Networks for Action Recognition in Videos , 2014, NIPS.
[35] Richard Szeliski,et al. A Database and Evaluation Methodology for Optical Flow , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[36] W. Richards,et al. Space-time disarray and visual awareness , 2012, i-Perception.
[37] Jitendra Malik,et al. Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[38] Matthew J. Hausknecht,et al. Beyond short snippets: Deep networks for video classification , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Michael J. Black,et al. Slow Flow: Exploiting High-Speed Cameras for Accurate and Diverse Optical Flow Reference Data , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).