YashaswiVermaYashaswi Verma

Areas of Interest: Computer Vision, Graphics.
 
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Address: International Institute of Information Technology Gachibowli Hyderbad 500032 India
 
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Personal Home Page: http://researchweb.iiit.ac.in/~yashaswi.verma/


Publications

Journal Publications:

  • Ayushi Dutta, Yashaswi Verma, and and C.V. Jawahar - Automatic image annotation: the quirks and what works Multimedia Tools and Applications An International Journal [PDF]

  • Yashaswi Verma and C.V. Jawahar - A support vector approach for cross-modal search of images and texts Computer Vision and Image Understanding 154 (2017): 48-63. [PDF]

  • Yashaswi Verma, C.V. Jawahar - Image Annotation by Propagating Labels from Semantic Neighbourhoods International Journal of Computer Vision (IJCV), 2016. [PDF]

Conference Publications:

  • Yashaswi Verma, C.V. Jawahar - A Robust Distance with Correlated Metric Learning for Multi-Instance Multi-Label Data Proceedings of the ACM Multimedia, 2016, Amsterdam, The Netherlands. [PDF]

  • Yashaswi Verma, C. V. Jawahar - A Probabilistic Approach for Image Retrieval Using Descriptive Textual Queries Proceedings of the ACM Multimedia, 26-30 Oct 2015, Brisbane, Australia. [PDF]

  • Yashaswi Verma, C.V. Jawahar - Exploring Locally Rigid Discriminative Patched for Learning Relative Attributes Proceedings of the 26th British Machine Vision Conference, 07-10 Sep 2015, Swansea, UK. [PDF]

  • Yashaswi Verma and C.V. Jawahar - Im2Text and Text2Im: Associating Images and Texts for Cross-Modal Retrieval Proceedings of British Machine Vision Conference, 01-05 Sep 2014, Nottingam, UK. [PDF]

  • Ramachandruni N. Sandeep, Yashaswi Verma and C.V. Jawahar - Relative Parts : Distinctive Parts of Learning Relative Attributes Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, 23-28 June 2014, Columbus, Ohio, USA. [PDF]

  • Sandeep, Ramachandruni N, Yashaswi Verma and C.V. Jawahar - Relative parts: Distinctive parts for learning relative attributes Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2014. [PDF]

  • Yashaswi Varma and C V Jawahar - Exploring SVM for Image Annotation in Presence of Confusing Labels Proceedings of the 24th British Machine Vision Conference, 09-13 Sep. 2013, Bristol, UK. [PDF]

  • Yashaswi Verma, Ankush Gupta, Prashanth Mannem and C.V. Jawahar - Generating image descriptions using semantic similarities in the output space Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2013. [PDF]

  • Yashaswi Verma and C V Jawahar - Neti Neti: In Search of Deity Proceedings of the 8th Indian Conference on Vision, Graphics and Image Processing, 16-19 Dec. 2012, Bombay, India. [PDF]

  • Yashaswi Varma and C V Jawahar - Image Annotation using Metric Learning in Semantic Neighbourhoods Proceedings of 12th European Conference on Computer Vision, 7-13 Oct. 2012, Print ISBN 978-3-642-33711--6, Vol. ECCV 2012, Part-III, LNCS 7574, pp. 114-128, Firenze, Italy. [PDF]

  • Ankush Gupta, Yashaswi Verma and C.V. Jawahar - Choosing Linguistics over Vision to Describe Images AAAI. 2012. [PDF]


Projects

relativeattributesLearning relative attributes using parts

People Involved :Ramachandruni N Sandeep, Yashaswi Verma, C. V. Jawahar

Our aim is to learn relative attributes using local parts that are shared across categories. First, instead of using a global representation, we introduce a part-based representation combining a pair of images that specifically compares corresponding parts. Then, with each part we associate a locally adaptive “significance coefficient” that represents its discriminative ability with respect to a particular attribute. For each attribute, the significance-coefficients are learned simultaneously with a max-margin ranking model in an iterative manner. Compared to the baseline method , the new method is shown to achieve significant improvements in relative attribute prediction accuracy. Additionally, it is also shown to improve relative feedback based interactive image search.

 

imageAnnotation Image Annotation

People Involved :Yashaswi Verma, C V Jawahar

In many real-life scenarios, an object can be categorized into multiple categories. E.g., a newspaper column can be tagged as "political", "election", "democracy"; an image may contain "tiger", "grass", "river"; and so on. These are instances of multi-label classification, which deals with the task of associating multiple labels with single data. Automatic image annotation is a multi-label classification problem that aims at associating a set of text with an image that describes its semantics.

 

praveenkrishnanPraveen Krishnan

Areas of Interest: Document Image Analysis, Deep Learning and Computer Vision.
 
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Address: CVIT, IIIT-H
 
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AnandMishraAnand Mishra

Areas of Interest: Computer Vision, Graphics.
 
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Address: CVIT, IIIT-H
 
Phone:

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:

  • 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.

ParikshitVishwasSakurikarParikshit Vishwas Sakurikar

Areas of Interest: Computer Vision, Graphics.
 
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Address: CVIT, IIIT-H
 
Phone:

ArunavaChakravartyArunava Chakravarty

Areas of Interest: Computer Vision, Graphics.
 
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Address: CVIT, IIIT-H
 
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