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P. Narayanan

6 papers hereh-index 151.2k citations38 works total

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

author position
  • first author1
  • middle author3
  • last author2

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.PL1
  • eess.AS1
same name
  • P. Narayanan — 3 papers
  • P. Narayanan — 2 papers, h 29
  • P. Narayanan — 2 papers, h 2
  • P. Narayanan — 2 papers, h 8

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
20182021
most citedHierarchical Sequence to Sequence Voice Conversion with Limited Data

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

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2021

Full-Velocity Radar Returns by Radar-Camera Fusion

Yunfei Long, Daniel Morris, Xiaoming Liu +3

A distinctive feature of Doppler radar is the measurement of velocity in the radial direction for radar points. However, the missing tangential velocity component hampers object ve…

cs.CV2021★ 1 cited

Radar-Camera Pixel Depth Association for Depth Completion

Yunfei Long, Daniel Morris, Xiaoming Liu +3

While radar and video data can be readily fused at the detection level, fusing them at the pixel level is potentially more beneficial. This is also more challenging in part due to…

cs.CV2020★ 2 cited

On the Role of Receptive Field in Unsupervised Sim-to-Real Image Translation

Nikita Jaipuria, Shubh Gupta, Praveen Narayanan +1

Generative Adversarial Networks (GANs) are now widely used for photo-realistic image synthesis. In applications where a simulated image needs to be translated into a realistic imag…

cs.CV2019

GEN-SLAM: Generative Modeling for Monocular Simultaneous Localization and Mapping

Punarjay Chakravarty, Praveen Narayanan, Tom Roussel

We present a Deep Learning based system for the twin tasks of localization and obstacle avoidance essential to any mobile robot. Our system learns from conventional geometric SLAM,…

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