World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
54
Citations
16141
World Ranking
4472
National Ranking
2091

Overview

R. Manmatha is affiliated with Amazon in the United States and has an extensive research portfolio primarily in the field of Computer Science. Their work spans several subfields, with a strong emphasis on Computer Vision and Pattern Recognition as well as Artificial Intelligence.

The scientist's research covers a variety of specialized topics, including:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Handwritten Text Recognition Techniques
  • Natural Language Processing Techniques
  • Topic Modeling
  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications

Frequent coauthors collaborating with R. Manmatha are:

  • Srikar Appalaraju
  • Chongruo Wu
  • Yi Zhu
  • Yusheng Xie
  • Ashwin Swaminathan

R. Manmatha has contributed to numerous renowned publication venues, particularly:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Recent notable publications include:

  • "ResNeSt: Split-Attention Networks" (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • "DocFormer: End-to-End Transformer for Document Understanding" (2021), 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "A Comprehensive Study of Deep Video Action Recognition" (2020), arXiv (Cornell University)
  • "Improving Semantic Segmentation via Efficient Self-Training" (2021), IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "LaTr: Layout-Aware Transformer for Scene-Text VQA" (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

The body of work by R. Manmatha demonstrates a consistent focus on advancing methods in object recognition, document understanding, and video analysis through the application of deep learning and transformer architectures.

Best Publications

  • Automatic image annotation and retrieval using cross-media relevance models

    J. Jeon;V. Lavrenko;R. Manmatha

  • ResNeSt: Split-Attention Networks

    Hang Zhang;Chongruo Wu;Zhongyue Zhang;Yi Zhu

  • Multiple Bernoulli relevance models for image and video annotation

    S.L. Feng;R. Manmatha;V. Lavrenko

  • A Model for Learning the Semantics of Pictures

    Victor Lavrenko;R. Manmatha;Jiwoon Jeon

  • Sampling Matters in Deep Embedding Learning

    R. Manmatha;Chao-Yuan Wu;Alexander J. Smola;Philipp Krahenbuhl

  • Word image matching using dynamic time warping

    T.M. Rath;R. Manmatha

  • Textfinder: an automatic system to detect and recognize text in images

    V. Wu;R. Manmatha;E.M. Riseman

  • Word spotting for historical documents

    Toni M. Rath;R. Manmatha

  • Finding text in images

    Victor Wu;R. Manmatha;Edward M. Riseman

  • A Novel Word Spotting Method Based on Recurrent Neural Networks

    V. Frinken;A. Fischer;R. Manmatha;H. Bunke

  • Compressed Video Action Recognition

    Chao-Yuan Wu;Manzil Zaheer;Hexiang Hu;R. Manmatha

  • Word spotting: a new approach to indexing handwriting

    R. Manmatha;Chengfeng Han;E.M. Riseman

  • Holistic word recognition for handwritten historical documents

    V. Lavrenko;T.M. Rath;R. Manmatha

  • Features for word spotting in historical manuscripts

    T.M. Rath;R. Manmatha

  • Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002

    James Allan;Jay Aslam;Nicholas Belkin;Chris Buckley

  • Modeling score distributions for combining the outputs of search engines

    R. Manmatha;T. Rath;F. Feng

  • A scale space approach for automatically segmenting words from historical handwritten documents

    R. Manmatha;J.L. Rothfeder

  • DocFormer: End-to-End Transformer for Document Understanding

    Srikar Appalaraju;Bhavan Jasani;Bhargava Urala Kota;Yusheng Xie

  • Using Maximum Entropy for Automatic Image Annotation

    Jiwoon Jeon;R. Manmatha

  • A search engine for historical manuscript images

    Toni M. Rath;R. Manmatha;Victor Lavrenko

Frequent Co-Authors

James Allan
James Allan University of Massachusetts Amherst
Victor Lavrenko
Victor Lavrenko University of Edinburgh
Edward M. Riseman
Edward M. Riseman University of Massachusetts Amherst
Alexander J. Smola
Alexander J. Smola Amazon (United States)
C. V. Jawahar
C. V. Jawahar International Institute of Information Technology, Hyderabad
Mubarak Shah
Mubarak Shah University of Central Florida
Philipp Krähenbühl
Philipp Krähenbühl The University of Texas at Austin
Harpreet Sawhney
Harpreet Sawhney Microsoft (United States)
Alexander G. Hauptmann
Alexander G. Hauptmann Carnegie Mellon University
Ajay Divakaran
Ajay Divakaran SRI International

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