Ashish Shrivastava

According to our database, Ashish Shrivastava authored at least 28 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

VLM-KD: Knowledge Distillation from VLM for Long-Tail Visual Recognition.

Zaiwei Zhang, Gregory P. Meyer, Zhichao Lu, Ashish Shrivastava, Avinash Ravichandran, Eric M. Wolff

CoRR, 2024

InVi: Object Insertion In Videos Using Off-the-Shelf Diffusion Models.

Nirat Saini, Navaneeth Bodla, Ashish Shrivastava, Avinash Ravichandran, Xiao Zhang, Abhinav Shrivastava, Bharat Singh

CoRR, 2024

GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR.

Bharat Singh, Viveka Kulharia, Luyu Yang, Avinash Ravichandran, Ambrish Tyagi, Ashish Shrivastava

CoRR, 2024

2023

AptSim2Real: Approximately-Paired Sim-to-Real Image Translation.

Charles Y. Zhang, Ashish Shrivastava

CoRR, 2023

NOVA: NOvel View Augmentation for Neural Composition of Dynamic Objects.

Dakshit Agrawal, Jiajie Xu, Siva Karthik Mustikovela, Ioannis Gkioulekas, Ashish Shrivastava, Yuning Chai

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

SHIFT3D: Synthesizing Hard Inputs For Tricking 3D Detectors.

Hongge Chen, Zhao Chen, Gregory P. Meyer, Dennis Park, Carl Vondrick, Ashish Shrivastava, Yuning Chai

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

I see what you hear: a vision-inspired method to localize words.

Mohammad Samragh, Arnav Kundu, Ting-Yao Hu, Minsik Cho, Aman Chadha, Ashish Shrivastava, Oncel Tuzel, Devang Naik

CoRR, 2022

Style Equalization: Unsupervised Learning of Controllable Generative Sequence Models.

Jen-Hao Rick Chang, Ashish Shrivastava, Hema Koppula, Xiaoshuai Zhang, Oncel Tuzel

Proceedings of the International Conference on Machine Learning, 2022

SYNT++: Utilizing Imperfect Synthetic Data to Improve Speech Recognition.

Ting-Yao Hu, Mohammadreza Armandpour, Ashish Shrivastava, Jen-Hao Rick Chang, Hema Koppula, Oncel Tuzel

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Optimize What Matters: Training DNN-Hmm Keyword Spotting Model Using End Metric.

Ashish Shrivastava, Arnav Kundu, Chandra Dhir, Devang Naik, Oncel Tuzel

Proceedings of the IEEE International Conference on Acoustics, 2021

SapAugment: Learning A Sample Adaptive Policy for Data Augmentation.

Ting-Yao Hu, Ashish Shrivastava, Jen-Hao Rick Chang, Hema Koppula, Stefan Braun, Kyuyeon Hwang, Ozlem Kalinli, Oncel Tuzel

Proceedings of the IEEE International Conference on Acoustics, 2021

Implicit vs. Explicit Style Transfer? A Comparison of GAN Architectures for Continuous Path Keyboard Input Modeling.

Akash Mehra, Jerome R. Bellegarda, Ojas Bapat, Hema Koppula, Jen-Hao Rick Chang, Ashish Shrivastava, Oncel Tuzel

Proceedings of the 29th European Signal Processing Conference, 2021

2020

Generating virtual images for promoting visual artificial intelligence.

Kunfeng Wang, Fei-Yue Wang, Visvanathan Ramesh, Ashish Shrivastava, David Vázquez, Fuxin Li

Neurocomputing, 2020

Unsupervised Style and Content Separation by Minimizing Mutual Information for Speech Synthesis.

Ting-Yao Hu, Ashish Shrivastava, Oncel Tuzel, Chandra Dhir

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Learning Conditional Error Model for Simulated Time-Series Data.

Ashish Shrivastava, Oncel Tuzel

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018

Divide, Denoise, and Defend against Adversarial Attacks.

Seyed-Mohsen Moosavi-Dezfooli, Ashish Shrivastava, Oncel Tuzel

CoRR, 2018

2017

Learning from Simulated and Unsupervised Images through Adversarial Training.

Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, Russell Webb

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2015

Sparse Representation, Discriminative Dictionaries and Projections for Visual Classification.

Ashish Shrivastava

PhD thesis, 2015

Multiple kernel-based dictionary learning for weakly supervised classification.

Ashish Shrivastava, Jaishanker K. Pillai, Vishal M. Patel

Pattern Recognit., 2015

Non-linear dictionary learning with partially labeled data.

Ashish Shrivastava, Vishal M. Patel, Rama Chellappa

Pattern Recognit., 2015

Generalized Dictionaries for Multiple Instance Learning.

Ashish Shrivastava, Vishal M. Patel, Jaishanker K. Pillai, Rama Chellappa

Int. J. Comput. Vis., 2015

Class consistent multi-modal fusion with binary features.

Ashish Shrivastava, Mohammad Rastegari, Sumit Shekhar, Rama Chellappa, Larry S. Davis

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Multiple Kernel Learning for Sparse Representation-Based Classification.

Ashish Shrivastava, Vishal M. Patel, Ramalingam Chellappa

IEEE Trans. Image Process., 2014

Unsupervised domain adaptation using parallel transport on Grassmann manifold.

Ashish Shrivastava, Sumit Shekhar, Vishal M. Patel

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2014

Dictionary-based multiple instance learning.

Ashish Shrivastava, Jaishanker K. Pillai, Vishal M. Patel, Rama Chellappa

Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

2012

Segmenting "simple" objects using RGB-D.

Ajay K. Mishra, Ashish Shrivastava, Yiannis Aloimonos

Proceedings of the IEEE International Conference on Robotics and Automation, 2012

Learning discriminative dictionaries with partially labeled data.

Ashish Shrivastava, Jaishanker K. Pillai, Vishal M. Patel, Rama Chellappa

Proceedings of the 19th IEEE International Conference on Image Processing, 2012

Design of Non-Linear Discriminative Dictionaries for Image Classification.

Ashish Shrivastava, Hien Van Nguyen, Vishal M. Patel, Rama Chellappa

Proceedings of the Computer Vision - ACCV 2012, 2012