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Prajwal Gatti

Indian Institute of Technology Jodhpur

4 papers hereh-index 433 citations6 works total

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

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
affiliations
  • Indian Institute of Technology Jodhpur
Homepage
same name
  • Prajwal Gatti — 3 papers, h 2

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
20222025
most citedCOFAR: Commonsense and Factual Reasoning in Image Search

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2025

Composite Sketch+Text Queries for Retrieving Objects with Elusive Names and Complex Interactions

Prajwal Gatti, Kshitij Parikh, Dhriti Prasanna Paul +2

Non-native speakers with limited vocabulary often struggle to name specific objects despite being able to visualize them, e.g., people outside Australia searching for numbats. Furt…

cs.CV2025

Towards Making Flowchart Images Machine Interpretable

Shreya Shukla, Prajwal Gatti, Yogesh Kumar +2

Computer programming textbooks and software documentations often contain flowcharts to illustrate the flow of an algorithm or procedure. Modern OCR engines often tag these flowchar…

cs.CV2023

Show Me the World in My Language: Establishing the First Baseline for Scene-Text to Scene-Text Translation

Shreyas Vaidya, Arvind Kumar Sharma, Prajwal Gatti +1

In this work, we study the task of ``visually'' translating scene text from a source language (e.g., Hindi) to a target language (e.g., English). Visual translation involves not ju…

cs.CV2022★ 1 cited

COFAR: Commonsense and Factual Reasoning in Image Search

Prajwal Gatti, Abhirama Subramanyam Penamakuri, Revant Teotia +3

One characteristic that makes humans superior to modern artificially intelligent models is the ability to interpret images beyond what is visually apparent. Consider the following…

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