tl;dr

Note to prospective students: We hire PhD students in computer vision, machine learning, and related fields every year. Find more about the graduate program here.
If you are interested in working with me, mention my name in your research statement.

News

  • 10/20:
    Two papers accepted at 3DV 2020.
  • 08/20:
    Serving as an Area Chair (SPC) for AAAI 2021.
  • 07/20:
    Three papers accepted at ECCV 2020.
  • 07/20:
    One paper accepted at ICIP 2020.
  • 05/20:
    Serving as an Area Chair for WACV 2021.
  • 02/20:
    PatchVAE accepted at CVPR 2020.
  • 02/20:
    Kyungjun's paper won Best Paper Award (Applications) at WACV 2020!
  • 01/20:
    Serving as an Area Chair for CVPR 2021.
  • 12/19:
    One paper accepted at ICLR 2020.
  • 11/19:
    Two papers accepted at AAAI 2020.
  • 10/19:
    Two papers accepted at WACV 2020.
  • 07/19:
    EvalNorm accepted at ICCV 2019.
  • 02/19:
    One paper accepted at CVPR 2019.
view more ..

About me

I am an Assistant Professor in the Department of Computer Science at University of Maryland, College Park, with a joint appointment in the Institute of Advanced Computer Studies (UMIACS). Before this, I spent 1 year as a Visiting Research Scientist at Google Research.

In August 2017, I received my PhD in Robotics and Artificial Intelligence from the Robotics Institute, Carnegie Mellon University, where I was advised by Abhinav Gupta. My PhD thesis, Discovering and Leveraging Visual Structure for Large-scale Recognition, was supported by Microsoft Research PhD Fellowship for 2014-16.

Before joining PhD, I received my Masters from the Robotics Institute, under the supervision of Alyosha Efros and Martial Hebert. Prior to that, I received my BTech in Computer Science and Engineering from JIIT (Noida, India).

I have also enjoyed working with awesome researchers and engineers in industry, including internships at Google Research and Microsoft Research (details).

Copyright © 2017 All right reserved

Research Experience

August, 2018 - present

Assistant Professor

University of Maryland, College Park

Joint appointments in Department of Computer Science and Institute of Advanced Computer Studies (UMIACS).
(details to follow)

September, 2017 - August, 2018

Visiting Research Scientist - Google Research

(details to follow)

August, 2016 - July, 2017

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.

Education

August, 2012 - August, 2017

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.
Find my dissertation here.

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'.

Teaching Experience

Teaching Assistant 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

Area Chair

  • Conferences: CVPR'18, ECCV'18, CVPR'19, CVPR'21, AAAI'21, WACV'21

Reviewer

  • Conferences: CVPR'12-17/20, NIPS'12-15, ECCV'12/14/16/20, ICCV'11/13/15/17/19, ACCV'12-16, SIGGRAPH'14, AAAI'15, 3DV'14-15
  • Journals: IJCV, TPAMI, CVIU, TKDE

Department Services (Carnegie Mellon University)

Copyright © 2019 All right reserved

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

2020

Improved Modeling of 3D Shapes with Multi-view Depth Maps Kamal Gupta, Susmija Jabbireddy, Ketul Shah, Abhinav Shrivastava, Matthias Zwicker International Conference on 3D Vision (3DV), 2020 new oral presentation preprint
Depth Completion using a View-constrained Deep Prior Pallabi Ghosh, Vibhav Vineet, Larry S. Davis, Abhinav Shrivastava, Sudipta Sinha, Neel Joshi International Conference on 3D Vision (3DV), 2020 new preprint
Quantization Guided JPEG Artifact Correction Max Ehrlich, Ser-Nam Lim, Larry Davis, Abhinav Shrivastava European Conference on Computer Vision (ECCV), 2020 new bibtex / pdf / code / teaser video / technical video
A Generic Visualization Approach for Convolutional Neural Networks Ahmed Taha, Xitong Yang, Abhinav Shrivastava, Larry Davis European Conference on Computer Vision (ECCV), 2020 new bibtex / pdf / code / project page / video
Curriculum Manager for Source Selection in Multi-Source Domain Adaptation Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava European Conference on Computer Vision (ECCV), 2020 new bibtex / pdf
PatchVAE: Learning Local Latent Codes for Recognition Kamal Gupta, Saurabh Singh, Abhinav Shrivastava IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 new bibtex / pdf / code / project page / video
Layout Generation and Completion with Self-attention Kamal Gupta, Alessandro Achille, Justin Lazarow, Larry Davis, Vijay Mahadevan, Abhinav Shrivastava arXiv, 2020 preprint pdf
Group Ensemble: Learning an Ensemble of ConvNets in a single ConvNet Hao Chen, Abhinav Shrivastava arXiv, 2020 preprint pdf
All About Knowledge Graphs for Actions Pallabi Ghosh, Nirat Saini, Larry Davis, Abhinav Shrivastava arXiv, 2020 preprint pdf
End-to-end Learning of Compressible Features Saurabh Singh, Sami Abu-El-Haija, Nick Johnston, Johannes Ballé, Abhinav Shrivastava, George Toderici International Conference on Image Processing (ICIP), 2020 pdf
Scalable Model Compression by Entropy Penalized Reparameterization Deniz Oktay, Johannes Ballé, Saurabh Singh, Abhinav Shrivastava International Conference on Learning Representations (ICLR), 2020 pdf
Detecting Human-Object Interactions via Functional Generalization Ankan Bansal, Saketh Rambhatla, Abhinav Shrivastava, Rama Chellappa Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020 bibtex / pdf
Generate, Segment and Refine: Towards Generic Manipulation Segmentation Peng Zhou, Bor-Chun Chen, Xintong Han, Mahyar Najibi, Abhinav Shrivastava, Ser-Nam Lim, Larry Davis Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020 bibtex / pdf / code
Hand-Priming in Object Localization for Assistive Egocentric Vision Kyungjun Lee, Abhinav Shrivastava, Hernisa Kacorri IEEE & CVF Winter Conference on Applications of Computer Vision (WACV), 2020 oral presentation best paper award (applications) bibtex / pdf / video
Boosting Standard Classification Architectures Through a Ranking Regularizer Ahmed Taha, Yi-Ting Chen, Teruhisa Misu, Abhinav Shrivastava, Larry Davis IEEE & CVF Winter Conference on Applications of Computer Vision (WACV), 2020 bibtex / pdf / project page / code

2019 and earlier

EvalNorm: Estimating Batch Normalization Statistics for Evaluation Saurabh Singh, Abhinav Shrivastava IEEE International Conference on Computer Vision (ICCV), 2019 bibtex / pdf
Render4Completion: Synthesizing Multi-view Depth Maps for 3D Shape Completion Tao Hu, Zhizhong Han, Abhinav Shrivastava, Matthias Zwicker ICCV Workshops, Geometry Meets Deep Learning, 2019 pdf
Relational Action Forecasting Chen Sun, Abhinav Shrivastava, Carl Vondrick, Rahul Sukthankar, Kevin Murphy, Cordelia Schmid IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 bibtex / pdf
Actor-centric Relation Network Chen Sun, Abhinav Shrivastava, Carl Vondrick, Kevin Murphy, Rahul Sukthankar, Cordelia Schmid European Conference on Computer Vision (ECCV), 2018 bibtex / pdf
Tracking Emerges by Colorizing Videos Carl Vondrick, Abhinav Shrivastava, Alireza Fathi, Sergio Guadarrama, Kevin Murphy European Conference on Computer Vision (ECCV), 2018 bibtex / pdf
In Media: Google AI Blog
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era Chen Sun, Abhinav Shrivastava, Saurabh Singh, Abhinav Gupta IEEE International Conference on Computer Vision (ICCV), 2017 spotlight presentation bibtex / pdf
In Media: Google Research Blog, Wired
A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection Xiaolong Wang, Abhinav Shrivastava, Abhinav Gupta IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 bibtex / pdf / code
Contextual Priming and Feedback for Faster R-CNN Abhinav Shrivastava, Abhinav Gupta European Conference on Computer Vision (ECCV), 2016 bibtex / pdf / poster
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) In Media: CNN, Discover Magazine, Newsweek, Forbes, Yahoo! News, BBC News, AP, Business Insider, Slashdot, Engadget, Techradar
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)

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 © 2019 All right reserved

Selected Awards and Honors

  • Best Paper Award (Applications), IEEE Winter Conference on Applications of Computer Vision; 2020
  • Outstanding Reviewer Award, IEEE CVPR; 2015
  • 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

Top-down Mechanisms in Bottom-up Deep Networks
    workshop
  • Workshop on Deep Learning, University of Maryland, College Park; May 2017
The Small and the Rare: the Twin Menace of Visual Recognition
    research tech talk
  • Faceook AI Research (FAIR); Jun. 2017

  • research tech talk
  • 4Catalyzer; Jun. 2017

  • colloqium
  • CS Colloqium, University of Maryland, College Park; Mar. 2017

  • seminar
  • GRASP Seminar, University of Pennsylvania; Feb. 2017
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 © 2017 All right reserved