(from Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri, Learning Spatiotemporal Features with 3D Convolutional Networks, ICCV15'. )
- C3D, Facebook AI Research [Paper] [Project Page] Hao
- Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri,
Learning Spatiotemporal Features with 3D Convolutional Networks, ICCV15'. - CNN with VLAD, The University of Queensland [Paper] Hao
- Zhongwen Xu, Yi Yang, Alexander G. Hauptmann,
A Discriminative CNN Video Representation for Event Detection, CVPR15'.
(from Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Pal, Hugo Larochelle, Aaron Courville, Describing Videos by Exploiting Temporal Structure, ICCV15'. )
- HRNE, Zhejiang University [Paper] Hao
- Pingbo Pan, Zhongwen Xu, Yi Yang, Fei Wu, Yueting Zhuang,
Hierarchical Recurrent Neural Encoder for Video Representation with Application to Captioning, arXiv:1511.03476. - LSTM with CNN+3DCNN & Attention Mechanism, Universite ́ de Montre ́al [Paper] Hao
- Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Pal, Hugo Larochelle, Aaron Courville,
Describing Videos by Exploiting Temporal Structure, ICCV15'. - Video caption via LSTM, UT Austin [Paper] [Project Page] Hao
- Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond Mooney, Kate Saenko,
Translating Videos to Natural Language Using Deep Recurrent Neural Networks, ICCV15'. - LSTM-E, Microsoft Research, Beijing [Paper] Hao
- Yingwei Pan, Tao Mei, Ting Yao, Houqiang Li, Yong Rui,
Jointly Modeling Embedding and Translation to Bridge Video and Language, arXiv:1505.01861. - p-RNN, Purdue University, Baidu Research - Institute of Deep Learning [Paper] Hao
- Haonan Yu, Jiang Wang, Zhiheng Huang, Yi Yang, Wei Xu,
Video Paragraph Captioning using Hierarchical Recurrent Neural Networks, arXiv:1510.07712.
- WristCam System, The University of Tokyo [Paper] JamesChan
- Katsunori Ohnishi, Atsushi Kanehira, Asako Kanezaki, Tatsuya Harada,
ecognizing Activities of Daily Living with a Wrist-mounted Camera, arXiv:1511.06783v1.
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Farneback's algorithm : Two-Frame Motion Estimation Based on Polynomial Expansion[PAPER] jimcheng *Joao F. Henriques Pedro Martins Rui Caseiro Jorge Batista˜,Institute of Systems and Robotics University of Coimbra -
LEAR PROJECT of deep and epic flow [PROJECT PAGE] *
DeepMatching: Deep Convolutional Matching. DeepMatching was recently used to improve the estimation of optical flow in several methods like DeepFlow and EpicFlow (joint work with Philippe Weinzaepfel, Zaid Harchaoui, Cordelia Schmid). -
DeepFlow: Large displacement optical flow with deep matching[PAPER] jimcheng *Philippe Weinzaepfel, J´erˆome Revaud, Zaid Harchaoui, Cordelia Schmid. ICCV, Dec 2013, Sydney, Australia. IEEE, pp.1385-1392, 2013, <10.1109/ICCV.2013.175>. -
EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow[PAPER] jimcheng *Jerome Revaud, Philippe Weinzaepfel, Zaid Harchaoui, Cordelia Schmid. CVPR, Jun 2015, Boston, United States.
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Parallel Architecture for Hierarchical Optical Flow Estimation Based on FPGA[PAPER] jimcheng *Francisco Barranco, Matteo Tomasi, Javier Diaz, Mauricio Vanegas, and Eduardo Ros, IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, VOL. 20, NO. 6, pp.1058-1067, JUNE 2012. -
Efficient Hardware Implementation of the Horn-Schunck Algorithm for High-Resolution Real-Time Dense Optical Flow Sensor[PAPER] jimcheng *Mateusz Komorkiewicz *, Tomasz Kryjak and Marek Gorgon, AGH University of Science and Technology, al. Sensors 2014, 14, 2860-2891; doi:10.3390/s140202860. -
Caffe con Troll: Shallow Ideas to Speed Up Deep Learning[PAPER] jimcheng *Stefan Hadjis† Firas Abuzaid† Ce Zhang†‡ Christopher Ré, Stanford University, University of Wisconsin-Madison, arXiv:1504.04343v2 [cs.LG] 26 May 2015. -
cuDNN: Efficient Primitives for Deep Learning[PAPER] jimcheng *Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, NVIDIA, Santa Clara, CA 95050, arXiv:1410.0759v3 [cs.NE] 18 Dec 2014.