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  6. Rajvi Shah

RajviShahRajvi Shah

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://rajvishah.weebly.com/
 

Publications

  • Rajvi Shah, Visesh Chari and P.J. Narayanan - View-graph Selection Framework for SfM European Conference on Computer Vision (ECCV), 2018, Munich, Germany [PDF]

  • Saumya Rawat, Siddhartha Gairola, Rajvi Shah and P.J. Narayanan - Find Me a Sky: A Data-Driven Method for Color-Consistent Sky Search and Replacement International Conference on Multimedia Modeling 2018: 216-228 [PDF]

  • Ishit Mehta, Parikshit Sakurikar, Rajvi Shah, P J Narayanan -  SynCam: Capturing sub-frame synchronous media using smartphones IEEE International Conference on Multimedia and Expo (ICME-2017 ).[PDF]

  • Aditya Singh, Saurabh Saini, Rajvi Shah and P. J. Narayanan - Learning to hash-tag videos with Tag2Vec Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing. ACM, 2016. [PDF]

  • Aditya Singh, Saurabh Saini, Rajvi Shah and P J Narayanan - From Traditional to Modern : Domain Adaptation for Action Classification in Short Social Video Clips 38th German Conference on Pattern Recognition (GCPR 2016) Hannover, Germany, September 12-15 2016. [PDF]

  • Rajvi Shah, Vanshika Srivastava, P.J. Narayanan - Geometry-aware Feature Matching for Structure from Motion Applications Proceedings of the IEEE Winter Conferenc on Applications of Computer Vision, 06-09 Jan 2015, Waikoloa Beach, USA. [PDF]

  • Rajvi Shah, Aditya Deshpande, P.J. Narayanan - Multistage SFM: Revisiting Incremental Structure from Motion Proceedings of the International Conference on 3D Vision,08-11 Dec 2014, Tokyo, Japan.[PDF]

  • Rajvi Shah and P.J. Narayanan - Trajectory based Video Object Manipulation Proceedings of IEEE International Conference on Multimedia and Expo (ICME 2011),11-15 July, 2011, Barcelona, Spain. [PDF]

  • Rajvi Shah, P. J. Narayanan and Kishore Kothapalli - GPU-Accelerated Genetic Algorithms Proceedings of The 3rd Workshop on Parallel Architectures for Bio-inspired Algorithms(WPABA) in conjunction with Parallel Architectures for Compilation Techniques (PACT'10),11-15 Sep. 2010,Vienna, Austria. [PDF]


Projects

graphView-graph Selection Framework for Structure from Motion

People Involved : Rajvi Shah, Visesh Chari, and P J Narayanan

View-graph is an essential input to large-scale structure from motion (SfM) pipelines. Accuracy and efficiency of large-scale SfM is crucially dependent on the input view-graph. Inconsistent or inaccurate edges can lead to inferior or wrong reconstruction. Most SfM methods remove `undesirable' images and pairs using several fixed heuristic criteria, and propose tailor-made solutions to achieve specific reconstruction objectives such as efficiency, accuracy, or disambiguation.

 

urdu_cnnFind me a sky : a data-driven method for color-consistent sky search & replacement

People Involved : Saumya Rawat, Siddhartha Gairola, Rajvi Shah, and P J Narayanan

Replacing overexposed or dull skies in outdoor photographs is a desirable photo manipulation. It is often necessary to color correct the foreground after replacement to make it consistent with the new sky. Methods have been proposed to automate the process of sky replacement and color correction. However, many times a color correction is unwanted by the artist or may produce unrealistic results.

 

sfm cover Exploiting SfM Data from Community Collections

People Involved : Aditya Singh, Apurva Kumar, Krishna Kumar Singh, Kaustav Kundu, Rajvi Shah, Aditya Deshpande, Shubham Gupta, Siddharth Choudhary and P J Narayanan

Progress in the field of 3D Computer Vision has led to the development of robust SfM (Structure from Motion) algorithms. These SfM algorithms, allow us to build 3D models of the monuments using community photo collections. We work on improving the speed and accuracy of these SfM algorithms and also on developing tools that use the rich geometry present in the SfM datasets.

 

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