CVIT CVIT
CVIT CVIT
  • Home
  • People
    • Faculty
    • Staff
    • PhD Students
    • MS Students
    • Alumni
    • Post-doctoral
    • Honours Student
  • Research
    • Publications
    • Journals
    • Books
    • MS Thesis
    • PhD Thesis
    • Projects
    • Resources
  • Events
    • Talks and Visits
    • Major Events
    • Visitors
    • Summer Schools
  • Gallery
  • News & Updates
    • News
    • Blog
    • Newsletter
    • Past Announcements
  • Contact Us
  • Login
  1. You are here:  
  2. Home
  3. People
  4. PhD Students
  5. PhD Students
  6. Anand Mishra

AnandMishraAnand Mishra

Areas of Interest: Computer Vision, Graphics.
 
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.
 
Address: CVIT, IIIT-H
 
Phone:
Personal Home Page: http://researchweb.iiit.ac.in/~anand.mishra/

Publications

Journal Publication:

  • Anand Mishra, Karteek Alahari and C.V. Jawahar - Unsupervised refinement of color and stroke features for text binarization International Journal on Document Analysis and Recognition (IJDAR) (2017): 1-17. [PDF]

  • Anand Mishra, Karteek Alahari and C. V. Jawahar - Enhancing energy minimization framework for scene text recognition with top-down cues - Computer Vision and Image Understanding (CVIU 2016), volume 145, pages 30–42, 2016. [PDF]

Conference Publication:

  • Suyash Maniyar, Vishvesh Trivedi, Ajoy Mondal, Anand Mishra, and C V Jawahar -  AI-Generated Lecture Slides for Improving Slide Element Detection and Retrieval International Conference on Document Analysis and Recognition (ICDAR), 2025 [ PDF ]

  • Ashutosh Mishra, Shyam Nandan Rai, Anand Mishra and C. V. Jawahar, IIIT-CFW: A Benchmark Database of Cartoon Faces in the Wild, 1st workshop on visual analysis and sketch (ECCVW) 2016. [PDF]

  • Ajeet Kumar Singh, Anand Mishra, Pranav Dabral and C V Jawahar - A Simple and Effective Solution for Script Identification in the Wild - Proceedings of 12th IAPR International Workshop on Document Analysis Systems (DAS'16), 11-14 April, 2016, Santorini, Greece. [PDF]

  • Sirnam Swetha, Anand Mishra, Guruprasad M. Hegde and C. V. Jawahar - Efficient Object Annotation for Surveillance and Automotive Applications - Proceedings of the IEEE Winter Conference on Applications of Computer Vision Workshop (WACVW 2016), March 7-9, 2016. [PDF]

  • Udit Roy, Anand Mishra, Karteek Alahari, C.V. Jawahar - Scene Text Recognition and Retrieval for Large Lexicons Proceedings of the 12th Asian Conference on Computer Vision,01-05 Nov 2014, Singapore. [PDF] [Abstract] [Poster] [Lexicons] [bibtex]

  • Anand Mishra, Karteek Alahari and C V Jawahar - Image Retrieval using Textual Cues Proceedings of International Conference on Computer Vision, 1-8th Dec.2013, Sydney, Australia. [Pdf] [Abstract] [Project page][bibtex]

  • Vijay Kumar, Amit Bansal, Goutam Hari Tulsiyan, Anand Mishra, Anoop M. Namboodiri, C V Jawahar - Sparse Document Image Coding for Restoration Proceedings of the 12th International Conference on Document Analysis and Recognition, 25-28 Aug. 2013, Washington DC, USA. [PDF]

  • Vibhor Goel, Anand Mishra, Karteek Alahari, C V Jawahar - Whole is Greater than Sum of Parts: Recognizing Scene Text Words Proceedings of the 12th International Conference on Document Analysis and Recognition, 25-28 Aug. 2013, Washington DC, USA. [PDF] [Abstract] [bibtex]

  • Deepan Gupta, Vaidehi Chhajer, Anand Mishra, C V Jawahar - A Non-local MRF model for Heritage Architectural Image Completion Proceedings of the 8th Indian Conference on Vision, Graphics and Image Processing, 16-19 Dec. 2012, Bombay, India. [PDF]

  • Anand Mishra, Karteek Alahari and C V Jawahar - Scene Text Recognition using Higher Order Language Priors Proceedings of British Machine Vision Conference, 3-7 Sep. 2012, Guildford, UK. [PDF] [Abstract] [Slides] [bibtex]

  • Anand Mishra, Karteek Alahari and C V Jawahar - Top-down and Bottom-up Cues for Scene Text Recognition Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 16-21 June 2012, pp. 2287-2294, Providence RI, USA. [PDF] [Abstract] [Poster] [bibtex]

  • Anand Mishra, Naveen Sankaran, Viresh Ranjan and C.V. Jawahar - Automatic localization and correction of line segmentation errors Proceeding of the workshop on Document Analysis and Recognition. ACM, 2012. [PDF]

  • Dheeraj Mundhra, Anand Mishra and C.V. Jawahar - Automatic Localization of Page Segmentation Errors Proceedings of Joint Workshop on Multilingual OCR and Analytics for Noisy Unstructured Text Data (J-MOCR-AND),17 September, 2011, Beijing, China. [PDF]

  • Anand Mishra, Karteek Alahari and C.V. Jawahar - An MRF Model for Binarization of Natural Scene Text Proceedings of 11th International Conference on Document Analysis and Recognition (ICDAR 2011),18-21 September, 2011, Beijing, China. [PDF] [Abstract] [Slides] [bibtex]

 


Projects

cartoonProPageThe IIIT-CFW dataset

People Involved : Ashutosh Mishra, Shyam Nandan Rai, Anand Mishra, C. V. Jawahar

The IIIT-CFW is database for the cartoon faces in the wild. It is harvested from Google image search. Query words such as Obama + cartoon, Modi + cartoon, and so on were used to collect cartoon images of 100 public figures. The dataset contains 8928 annotated cartoon faces of famous personalities of the world with varying profession. Additionally, we also provide 1000 real faces of the public figure to study cross modal retrieval tasks, such as, Photo2Cartoon retrieval. The IIIT-CFW can be used for the study spectrum of problems as discussed in our ECCVW paper.

 

SceneTextUnderstanding Scene Text Understanding

People Involved :Udit Roy, Anand Mishra, Karteek Alahari and C.V. Jawahar

Scene text recognition has gained significant attention from the computer vision community in recent years. Often images contain text which gives rich and useful information about their content. Recognizing such text is a challenging problem, even more so than the recognition of scanned documents. Scene text exhibits a large variability in appearances, and can prove to be challenging even for the state-of-the-art OCR methods. Many scene understanding methods recognize objects and regions like roads, trees, sky etc in the image successfully, but tend to ignore the text on the sign board. Our goal is to fill this gap in understanding the scene.

  • Anand Mishra
  • Publications
  • Projects