QTTNet: Quantized tensor train neural networks for 3D object and video recognition
- 1 September 2021
- journal article
- research article
- Published by Elsevier in Neural Networks
- Vol. 141, 420-432
Abstract
No abstract availableKeywords
This publication has 16 references indexed in Scilit:
- Activity Recognition Using Temporal Optical Flow Convolutional Features and Multilayer LSTMIEEE Transactions on Industrial Electronics, 2018
- Long-Term Temporal Convolutions for Action RecognitionIEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
- Regularized Computation of Approximate Pseudoinverse of Large Matrices Using Low-Rank Tensor Train DecompositionsSIAM Journal on Matrix Analysis and Applications, 2016
- DeepPano: Deep Panoramic Representation for 3-D Shape RecognitionIEEE Signal Processing Letters, 2015
- A Robust and Efficient Video Representation for Action RecognitionInternational Journal of Computer Vision, 2015
- Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysisIEEE Signal Processing Magazine, 2015
- Robust action recognition using local motion and group sparsityPattern Recognition, 2014
- Dense Trajectories and Motion Boundary Descriptors for Action RecognitionInternational Journal of Computer Vision, 2013
- 3D Convolutional Neural Networks for Human Action RecognitionIEEE Transactions on Pattern Analysis and Machine Intelligence, 2012
- Tensor-Train DecompositionSIAM Journal on Scientific Computing, 2011