Ashish Shrivastava
Cited by
Cited by
Learning from simulated and unsupervised images through adversarial training
A Shrivastava, T Pfister, O Tuzel, J Susskind, W Wang, R Webb
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Multiple kernel learning for sparse representation-based classification
A Shrivastava, VM Patel, R Chellappa
IEEE Transactions on Image Processing 23 (7), 3013-3024, 2014
Segmenting “simple” objects using RGB-D
AK Mishra, A Shrivastava, Y Aloimonos
2012 IEEE International Conference on Robotics and Automation, 4406-4413, 2012
Learning discriminative dictionaries with partially labeled data
A Shrivastava, JK Pillai, VM Patel, R Chellappa
2012 19th IEEE International Conference on Image Processing, 3113-3116, 2012
Generalized dictionaries for multiple instance learning
A Shrivastava, VM Patel, JK Pillai, R Chellappa
International Journal of Computer Vision 114 (2), 288-305, 2015
Unsupervised domain adaptation using parallel transport on Grassmann manifold
A Shrivastava, S Shekhar, VM Patel
IEEE winter conference on applications of computer vision, 277-284, 2014
Design of non-linear discriminative dictionaries for image classification
A Shrivastava, HV Nguyen, VM Patel, R Chellappa
Asian Conference on Computer Vision, 660-674, 2012
Non-linear dictionary learning with partially labeled data
A Shrivastava, VM Patel, R Chellappa
Pattern Recognition 48 (11), 3283-3292, 2015
Divide, denoise, and defend against adversarial attacks
SM Moosavi-Dezfooli, A Shrivastava, O Tuzel
arXiv preprint arXiv:1802.06806, 2018
Multiple kernel-based dictionary learning for weakly supervised classification
A Shrivastava, JK Pillai, VM Patel
Pattern Recognition 48 (8), 2667-2675, 2015
Dictionary-based multiple instance learning
A Shrivastava, JK Pillai, VM Patel, R Chellappa
2014 IEEE International Conference on Image Processing (ICIP), 160-164, 2014
Class consistent multi-modal fusion with binary features
A Shrivastava, M Rastegari, S Shekhar, R Chellappa, LS Davis
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
Method for generating high-resolution images using regression patterns
F Porikli, A Shrivastava, J Thornton
US Patent 9,734,558, 2017
Unsupervised style and content separation by minimizing mutual information for speech synthesis
TY Hu, A Shrivastava, O Tuzel, C Dhir
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
SapAugment: Learning A Sample Adaptive Policy for Data Augmentation
TY Hu, A Shrivastava, R Chang, H Koppula, S Braun, K Hwang, O Kalini, ...
arXiv preprint arXiv:2011.01156, 2020
Defense against adversarial attacks on neural networks
A Shrivastava, CO Tuzel, S Moosavi-Dezfooli
US Patent 10,984,272, 2021
Optimize what matters: Training DNN-HMM Keyword Spotting Model Using End Metric
A Shrivastava, A Kundu, C Dhir, D Naik, O Tuzel
arXiv preprint arXiv:2011.01151, 2020
Generating virtual images for promoting visual artificial intelligence
K Wang, FY Wang, V Ramesh, A Shrivastava, D Vazquez, F Li
Neurocomputing 394, 112-113, 2020
Learning Conditional Error Model for Simulated Time-Series Data.
A Shrivastava, O Tuzel
CVPR Workshops, 91-94, 2019
Sparse representation, discriminative dictionaries and projections for visual classification
A Shrivastava
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