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researcher

A. Shrivastava

11 papers hereh-index 162.6k citations52 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author7
  • last author1

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.AR2
  • eess.AS2
  • cs.CL1
  • cs.LG1
  • cs.SD1
same name
  • A. Shrivastava — 21 papers, h 24
  • A. Shrivastava — 4 papers, h 10
  • A. Shrivastava — 2 papers
  • A. Shrivastava — 2 papers, h 2
  • A. Shrivastava — 1 paper, h 6
  • A. Shrivastava — 1 paper, h 9

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182023
most citedSynt++: Utilizing Imperfect Synthetic Data to Improve Speech Recognition

4 citations · 6 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023

NOVA: NOvel View Augmentation for Neural Composition of Dynamic Objects

Dakshit Agrawal, Jiajie Xu, Siva Karthik Mustikovela +3

We propose a novel-view augmentation (NOVA) strategy to train NeRFs for photo-realistic 3D composition of dynamic objects in a static scene. Compared to prior work, our framework s…

cs.CV2023★ 1 cited

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

Charles Y Zhang, Ashish Shrivastava

Advancements in graphics technology has increased the use of simulated data for training machine learning models. However, the simulated data often differs from real-world data, cr…

cs.CV2022

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

Mohammad Samragh, Arnav Kundu, Ting-Yao Hu +5

This paper explores the possibility of using visual object detection techniques for word localization in speech data. Object detection has been thoroughly studied in the contempora…

cs.CV2018

Divide, Denoise, and Defend against Adversarial Attacks

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

Deep neural networks, although shown to be a successful class of machine learning algorithms, are known to be extremely unstable to adversarial perturbations. Improving the robustn…

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