News

  • 12/16:
    Our work on Top-down Modulation achieves state-of-the-art single model performance of 36.8 AP on COCO object detection task, without any bells and whistles! Read more here.
  • 10/16:
    Our team stood 4th in the 2016 COCO object detection challenge (leaderboard, see Challenge2016), using the Priming and Feedback model from our ECCV paper (with some bells and whistles). It is the best VGG16 single-model entry, above a couple of ResNet entries!
  • 08/16:
    Code released for OHEM.
  • 07/16:
  • 03/16:
  • 03/16:
    A hackathon project during my internship at Microsoft Research is the basis of the 'Seeing AI' product. During my Masters, I worked on a similar project on Assistive Technologies using a first person vision device (read more).
  • 12/15:
    Our team stood 4th in the 2015 MS COCO object detection challenge (leaderboard, see Challenge2015). Our entry used hard example mining to train Fast R-CNN (and added some bells and whistles).

n-th year PhD student

I am a PhD candidate in Robotics and Artificial Intelligence at the Robotics Institute, Carnegie Mellon University, advised by Abhinav Gupta. I also collaborate frequently with Alyosha Efros and Martial Hebert. My research revolves around scalable visual recognition algorithms for discovering and harnessing structure in large-scale data.

During my PhD, I was supported by Microsoft Research PhD Fellowship for 2014-16. I have also enjoyed working with awesome researchers and engineers in industry, including internships at Google Research and Microsoft Research (details).

Before joining PhD, I received my Masters from the Robotics Institute, under the supervision of Alyosha Efros and Martial Hebert. Prior to that, I did my undergrad in Computer Science and Engineering from JIIT, Noida (India), where my thesis was on 'A Hypermedia-development Tool for Movie-based Comic-strip Rendering'.

Copyright © 2016 All right reserved

Education

August, 2012 - Present

PhD, Artificial Intelligence

Robotics Institute, Carnegie Mellon University

Working on discovering the underlying regularities, or structure, in our visual world and leveraging it in large-scale recognition algorithms and systems. This work spans a wide range of recognition tasks, and includes frequent collaborations with researchers from both academia and industry.

August, 2010 - December, 2011

M.S., Aritificial Intelligence

Robotics Institute, Carnegie Mellon University

Worked on data-driven visual similarity for image matching and retrieval, real-time assistive systems, and object detection.

July, 2006 - May, 2010

BTech., Computer Science and Engineering

Jaypee Institute of Information Technology

Thesis on 'A Hypermedia-development Tool for Movie-based Comic-strip Rendering'.

Research Experience

August, 2016- Present

Research Assistant - Google Research

Working with Abhinav Gupta, Rahul Sukthankar, and Jitendra Malik on incorporating feedback in object detection models.

Summer, 2015

Research Intern - Microsoft Research

Worked with Ross Girshick and Larry Zitnick on object detection and semi-supervised learning.

Summer, 2013

Research Intern - Google Research

Worked with Mark Segal, Rahul Sukthankar and Thomas Leung on incorporating image geometry in deep neural networks.

Summer, 2012

Research Intern -Microsoft Research

Worked on large-scale indexing and nearest-neighbor search for high-dimensional data with Sanjeev Mehrotra and Jin Li.

Fall, 2010

Research Associate III -- Robotics Institute, Carnegie Mellon University

Continued Masters research on image matching and retrieval, real-time assistive systems, and object detection; and worked on large-scale semi-supervised learning algorithm.

Teaching Experience

  • Teaching Assistant, Geometry-based Methods in Vision, CMU; Spring 2013
  • Teaching Assistant, Data Structures, JIIT; 2008-09
  • Teaching Assistant, Microprocessors and Controllers, JIIT; 2008-09

Department Services (Carnegie Mellon University)

Reviewer

  • Conferences: CVPR'12-17, NIPS'12-15, ECCV'12-16, ICCV'11-15, ACCV'12-16, SIGGRAPH'14, AAAI'15, 3DV'14-15
  • Journals: IJCV, TPAMI, CVIU, TKDE

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Interests

I enjoy working on artificial intelligence, particularly computer vision and machine learning; and my research interests include related fields such as robotics, graphics, natural language processing, human-computer interaction, systems, data mining, and cognitive and computational neuroscience.

My long term goal is to equip machines with visual perception abilities, which enables them to understand and respond to their surroundings.

Publications

Beyond Skip Connections: Top-Down Modulation for Object Detection Abhinav Shrivastava, Rahul Sukthankar, Jitendra Malik, Abhinav Gupta In submission at IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 new under review bibtex / pdf / code (coming soon)
A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection Xiaolong Wang, Abhinav Shrivastava, Abhinav Gupta In submission at IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 new under review bibtex / pdf / code (coming soon)
Contextual Priming and Feedback for Faster R-CNN Abhinav Shrivastava, Abhinav Gupta European Conference on Computer Vision (ECCV), 2016 new bibtex / pdf / poster / code (coming soon)
Training Region-based Object Detectors with Online Hard Example Mining Abhinav Shrivastava, Abhinav Gupta, Ross Girshick IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 oral presentation bibtex / pdf / code / video / poster / slides (pptx)
Cross-stitch Networks for Multi-task Learning Ishan Misra*, Abhinav Shrivastava*, Abhinav Gupta, Martial Hebert (*equal contribution) IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 spotlight presentation bibtex / pdf / poster / slides
Watch and Learn: Semi-supervised Learning of Object Detectors from Videos Ishan Misra, Abhinav Shrivastava, Martial Hebert IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015 bibtex / pdf / project page / poster
Enriching Visual Knowledge Bases via Object Discovery and Segmentation Xinlei Chen, Abhinav Shrivastava, Abhinav Gupta IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014 bibtex / pdf / project page / code / poster / supplement
Data-driven Exemplar Model Selection Ishan Misra, Abhinav Shrivastava, Martial Hebert IEEE Winter Conference on Applications of Computer Vision (WACV), 2014 oral presentation best student paper award bibtex / pdf / project page / slides (pptx)
Building Part-based Object Detectors via 3D Geometry Abhinav Shrivastava, Abhinav Gupta IEEE International Conference on Computer Vision (ICCV), 2013 bibtex / pdf / project page
NEIL: Extracting Visual Knowledge from Web Data Xinlei Chen, Abhinav Shrivastava, Abhinav Gupta IEEE International Conference on Computer Vision (ICCV), 2013 oral presentation bibtex / pdf / project page / code / test code / video / poster / slides (pptx)
Constrained Semi-Supervised Learning using Attributes and Comparative Attributes Abhinav Shrivastava, Saurabh Singh, Abhinav Gupta European Conference on Computer Vision (ECCV), 2012 oral presentation bibtex / pdf / project page / video / slides (pptx)
Data-driven Visual Similarity for Cross-domain Image Matching Abhinav Shrivastava, Tomasz Malisiewicz, Abhinav Gupta, Alexei A. Efros ACM Transaction of Graphics, (Proceedings of SIGGRAPH Asia), 2011 oran presentation bibtex / pdf / project page / code / video / supplement / data / slides (pptx)

Invited Papers and Technical Reports

Real-time Household Object Detection from First-person's view using Exemplar-SVMs Abhinav Shrivastava, Abhinav Gupta, Alexei A. Efros In IEEE Workshop on Egocentric Vision at CVPR, 2012 extended abstract & poster project page, code and demo
Exemplar-SVMs for Visual Object Detection, Label Transfer and Image Retrieval Tomasz Malisiewicz, Abhinav Shrivastava, Abhinav Gupta, Alexei A. Efros In International Conference on Machine Learning (ICML), 2012 invited applications talk & extended abstract pdf / slides
Measuring and Increasing the capacity of Natural HOG Statistics Tinghui Zhou, Abhinav Shrivastava, Guillaume Obozinski, Abhinav Gupta, Alexei A. Efros Technical Report, Carnegie Mellon University MS thesis (T. Zhou) pdf / supplement
HOG and Spatial Convolution on SIMD Architecture Ishan Misra, Abhinav Shrivastava, Martial Hebert Technical Report, Carnegie Mellon University pdf / code

Copyright © 2016 All right reserved

Selected Awards and Honors

  • Microsoft Research Ph.D. Fellowship; 2014-16
  • CNNs Top-10 Ideas 2013 (Thinking Tech)
  • Best Student Paper Award, IEEE Winter Conference on Applications of Computer Vision; 2014
  • Selected for Google Graduate CS Forum; 2012
  • Research Highlight of the week, Computing Community Consortium; 2011
  • Vice Chancellor Gold Medal (awarded to Rank 1 out of 120), Dept. of Computer Science and Engineering, JIIT; 2006-10

Selected Talks, Seminars and Lectures

Training Region-based Object Detectors with Online Hard Example Mining
    conference
  • CVPR; Jun. 2016; video
NEIL: Extracting Visual Knowledge from Web Data
  • CMU VASC Seminar; Nov. 2013

  • conference
  • ICCV; Dec. 2013; video

  • course
  • Guest Lecture: Visual Recognition, University of Pittsburgh; Feb. 2015
Constrained Semi-Supervised Learning using Attributes and Comparative Attributes
  • CMU VASC Seminar; Sep. 2012

  • conference
  • ECCV; Dec. 2012; video

  • course
  • Guest Lecture: Visual Recognition, University of Pittsburgh; Feb. 2015
Data-driven Visual Similarity for Cross-domain Image Matching
    conference
  • SIGGRAPH Asia; Dec. 2011

  • course
  • Guest Lecture: Visual Recognition, University of Pittsburgh; Feb. 2015
Overview of Object Detection with historical context
    course req.
  • Learning-based Methods in Vision, CMU; Oct. 2013
Semantic vs. Visual Subcategories in Computer Vision and Neuroscience
    course req.
  • The Visual World as seen by the Neurons and Machines; Mar. 2014
Building Part-based Object Detectors via 3D Geometry
  • CMU VASC Seminar; Nov. 2013
Tutorial on Caffe toolbox
    course req.
  • Big Data Approaches in Vision, CMU; Sep. 2014
Vanishing Point Estimation, and applications to Scene-layout Estimation
    course
  • Guest Lecture, Geometry-based Methods in Vision, CMU; 2013-16
Indexing in High-dimensional spaces (for large-scale nearest neighbor search)
    industry
  • Bing, Microsoft; Aug. 2012

  • Tutorial, CMU; Sep. 2012
Tutorial and Workshop on Automated Robotics (Micro-mouse)
    course
  • Microprocessors and Controllers, JIIT; 2008-09

  • Guest Lecture, Computer Society of India (CSI) Week, IGIT, Indraprastha (IP) University; 2008

  • Guest Lecture, IEEE Week, NIEC; 2008

  • Workshop, IEEE Winter Academic Program, JIIT; 2008

Selected Robotics Competitions (undergrad)

  • Finalists, Robo-Relay, IIT, Kharagpur; 2008
  • Runner-up, Line Follower, Delhi College of Engineering; 2008
  • Finalist, Maze Ablaze, Delhi College of Engineering; 2008
  • Winner, Cross Terrain Racing, USIT, Indraprastha (IP) University (New Delhi); 2007
  • Winner, Trash Collection, IGIT, Indraprastha (IP) University (New Delhi); 2007
  • Runner-up, Chequered Flag, IGIT, Indraprastha (IP) University (New Delhi); 2007

Selected Positions Held (undergrad)

  • Technical Research Coordinator, Creativity and Innovation Cell in Robotics, JIIT; 2008-09
  • Sun Campus Ambassador (for Sun Microsystems Inc.), JIIT; 2008
  • President, JIIT Youth Club (student union), JIIT, 2008-09
  • Team Leader, Microsoft Go-Alive Challenge, JIIT; 2008
  • Treasurer, EBULLIENCE, JIIT; 2007
  • Chief Project Coordinator, Multimedia Project (2D Graphics) (managing more than 800 students), JIIT; 2007

Copyright © 2016 All right reserved