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researcher

P. Natarajan

8 papers hereh-index 201.4k citations55 works total

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

author position
  • middle author5
  • last author2

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.CL3
  • cs.SI1
same name
  • P. Natarajan — 193 papers, h 66
  • P. Natarajan — 47 papers, h 41
  • P. Natarajan — 21 papers, h 11
  • P. Natarajan — 20 papers, h 5
  • P. Natarajan — 8 papers, h 7
  • P. Natarajan — 1 paper, h 16

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
20202023
most citedAlexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems

64 citations · 92 across the 7 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023★ 1 cited

FashionNTM: Multi-turn Fashion Image Retrieval via Cascaded Memory

Anwesan Pal, Sahil Wadhwa, Ayush Jaiswal +5

Multi-turn textual feedback-based fashion image retrieval focuses on a real-world setting, where users can iteratively provide information to refine retrieval results until they fi…

cs.CV2023

MoMo: A shared encoder Model for text, image and multi-Modal representations

Rakesh Chada, Zhaoheng Zheng, Pradeep Natarajan

We propose a self-supervised shared encoder model that achieves strong results on several visual, language and multimodal benchmarks while being data, memory and run-time efficient…

cs.CV2021★ 4 cited

Style-Aware Normalized Loss for Improving Arbitrary Style Transfer

Jiaxin Cheng, Ayush Jaiswal, Yue Wu +2

Neural Style Transfer (NST) has quickly evolved from single-style to infinite-style models, also known as Arbitrary Style Transfer (AST). Although appealing results have been widel…

cs.CV2020

Class-agnostic Object Detection

Ayush Jaiswal, Yue Wu, Pradeep Natarajan +1

Object detection models perform well at localizing and classifying objects that they are shown during training. However, due to the difficulty and cost associated with creating and…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.