Computer Vision Scientist
SRI International
karan.sikka AT sri DOT com
Short CV
Google Scholar Page

I am a Computer Vision Scientist at Center for Vision Technologies, SRI International
in Princeton, New Jersey. I graduated with a PhD degree from Machine Perception Lab at UCSD and was advised by Dr. Marian Bartlett. Before joining UCSD, I completed my bachelor's in ECE at Indian Institute of Technology Guwahati. My research interest in general spans joint multimodal analytics and computer vision problems related to classification and detection in both images and videos. During my PhD I primarily worked on problem related to action classification in videos for both recognizing human facial behavior and human actions. At SRI I have developed innovative prototypes and algorithms pertaining to deep multimodal (vision, language and audio) learning for understanding social media structure and content under the DARPA M3I, AFRL MESA and ONR CEROSS programs.


  1. We are hiring Interns at SRI. Please drop an email if you wish to apply.
  2. Jul 2018 I was invited as a speaker at the MADIMA Workshop (4th International Workshop on Multimedia Assisted Dietary Management) held in conjuction with IJCAI and ECAI, Stockholm, Sweden. I presented our work on food classification and recent iFood challenge organized at CVPR 2018.
  3. Jul 2018: Our work on Zero-shot object detection was accepted at ECCV 2018. Visit the webpage for paper and more details.
  4. Jun 2018: Our work on "Understanding Visual Ads by Aligning Symbols and Objects using Co-Attention" is online now . In this work we proposed a novel weakly supervised learning algorithm that uses an iterative co-attention mechanism to effectively combine multiple references (semantic and symbolic) present in an image. This work was presented as workshop paper at CVPR 2018.
  5. Apr 2018: We are hosting the iFood 2018 challenge aimed at classifying fine-grained food categories in images. We have introduced a new dataset with 211 food categories for this challenge. This competition is part of the FGVC workshop being held at CVPR 2018. Please visit the Github page and Kaggle page for more details. This challenge is jointly organized by SRI International and Google.
  6. Apr 2018: Our recent work on Zero-shot object detection is online now. In this work we introduce and target the novel problem of detecting unseen objects in test images. We have tried to comprehensively study this problem and propose new experimental design to evaluate this problem. Visit the webpage for paper and more details.
  7. Dec 2017: Technical report on our work on combining Weakly and Webly supervised learning for classifying food images is available.
  8. Our prior work extending our CVPR 2016 paper on Latent Ordinal Model to Human Action Recognition has been accepted to IEEE TPAMI . Please find the paper here.
  9. AdaScan paper has been accepted to CVPR 2017.
  10. We have uploaded paper for our new work- AdaScan (Adaptive Scan Pooling) for human action classification in videos. AdaScan is a deep CNN that pools informative and discriminative frames in a single temporal scan of the video.
  11. I have joined the Vision and Learning group at SRI International in Princeton, New Jersey.
  12. I am have successfully defended on 15th August 2016 and here are the video as well as the presentation slides.
  13. Our paper extending our CVPR 2016 work has been uploaded to arXiv. This work extends LOMo algorithm and also evaluates it on human action classification. We provide extenstive qualitative and quantitative experiments. We have updated the project page.
  14. I had a wonderful and productive 2 week visit to Indian Institute of Technology Kanpur as a visiting researcher (16th May - 27th May 2016).
  15. Paper (Spotlight Presentation) accepted at Computer Vision and Pattern Recognition (CVPR) 2016, with Dr. Gaurav Sharma (Assistant Professor at Indian Institute of Technology Kanpur).
  16. Blog entry on my thesis and CVPR paper.
  17. Will be working as an Associate intern in Vision and Learning group at SRI International, Princeton from Jan-Mar 2016.
  18. Two Paper accepted in BMVC 2015 .
  19. Another article on Collaborative work on predicting Pain in pediatric population in Engadget Link
  20. Article on Collaborative work on predicting Pain in pediatric population in UCSD Heath Newsroom Link
  21. Paper on 'Automated Assessment of Children's Post-Operative Pain' accepted in Pediatrics journal. Collaborative work with Dr. Jeannie Huang, Dr. Kenneth Craig, Dr. Marian Bartlett, Alex Ahmed and Damariz Diaz.
  22. Group Expression paper (collaborative work with Dr. Abhinav Dhall et al.) accepted in IEEE FG 2015 .
  23. Finished my thesis proposal exam and advanced to candidacy.

Previous and Current Affiliations