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D-Index & Metrics

Computer Science

D-Index
99
Citations
60235
World Ranking
381
National Ranking
209

Research.com Recognitions

  • 2020 - IAPR J. K. Aggarwal Prize "For pioneering contributions to unsupervised and self-supervised learning in computer vision and robotics."
  • 2016 - Fellow of Alfred P. Sloan Foundation

Overview

Abhinav Gupta is affiliated with Carnegie Mellon University in the United States and primarily works within the field of Computer Science. Their research focuses extensively on areas including Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Control and Systems Engineering, and Economics and Econometrics.

Their work encompasses several specialized topics such as Reinforcement Learning in Robotics, Domain Adaptation and Few-Shot Learning, Multimodal Machine Learning Applications, Human Pose and Action Recognition, Robot Manipulation and Learning, Topic Modeling, and Machine Learning and Algorithms.

Among their recent papers are the following:

  • Object Goal Navigation using Goal-Oriented Semantic Exploration (2020), published in arXiv (Cornell University)
  • Hollywood in homes: Crowdsourcing data collection for activity understanding (2024), published in arXiv (Cornell University)
  • Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases (2020), published in arXiv (Cornell University)
  • International trade and social connectedness (2020), published in Journal of International Economics
  • Does Private Equity Investment in Healthcare Benefit Patients? Evidence from Nursing Homes (2021), published in SSRN Electronic Journal

Frequently collaborating with other researchers, Abhinav Gupta has worked with Shubham Tulsiani, Senthil Purushwalkam, Sabrina T Howell, Yufei Ye, and Pedro Morgado with multiple joint publications.

They have published notably in several venues:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Lecture Notes in Computer Science
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Gupta has been recognized with awards including the IAPR J. K. Aggarwal Prize in 2020, awarded for contributions to unsupervised and self-supervised learning in computer vision and robotics, and was named a Fellow of the Alfred P. Sloan Foundation in 2016.

Best Publications

  • Non-local Neural Networks

    Xiaolong Wang;Ross Girshick;Abhinav Gupta;Kaiming He

  • Unsupervised Visual Representation Learning by Context Prediction

    Carl Doersch;Abhinav Gupta;Alexei A. Efros

  • Revisiting Unreasonable Effectiveness of Data in Deep Learning Era

    Chen Sun;Abhinav Shrivastava;Saurabh Singh;Abhinav Gupta

  • Training Region-Based Object Detectors with Online Hard Example Mining

    Abhinav Shrivastava;Abhinav Gupta;Ross Girshick

  • The Visual Object Tracking VOT2016 Challenge Results

    Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg

  • Target-driven visual navigation in indoor scenes using deep reinforcement learning

    Yuke Zhu;Roozbeh Mottaghi;Eric Kolve;Joseph J. Lim

  • The Stanford Dash multiprocessor

    D. Lenoski;J. Laudon;K. Gharachorloo;W.-D. Weber

  • Cross-Stitch Networks for Multi-task Learning

    Ishan Misra;Abhinav Shrivastava;Abhinav Gupta;Martial Hebert

  • Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding

    Gunnar A. Sigurdsson;Gül Varol;Xiaolong Wang;Ali Farhadi;Ali Farhadi

  • Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours

    Lerrel Pinto;Abhinav Gupta

  • Unsupervised Learning of Visual Representations Using Videos

    Xiaolong Wang;Abhinav Gupta

  • Ensemble of exemplar-SVMs for object detection and beyond

    Tomasz Malisiewicz;Abhinav Gupta;Alexei A. Efros

  • Never-ending learning

    T. Mitchell;W. Cohen;E. Hruschka;P. Talukdar

  • What makes Paris look like Paris

    Carl Doersch;Saurabh Singh;Abhinav Gupta;Josef Sivic

  • Never-ending learning

    T. Mitchell;W. Cohen;E. Hruschka;P. Talukdar

  • Videos as Space-Time Region Graphs

    Xiaolong Wang;Abhinav Gupta

  • Complete computer system simulation: the SimOS approach

    M. Rosenblum;S.A. Herrod;E. Witchel;A. Gupta

  • Learning a Predictable and Generative Vector Representation for Objects

    Rohit Girdhar;David F. Fouhey;Mikel Rodriguez;Abhinav Gupta

  • Unsupervised Discovery of Mid-Level Discriminative Patches

    Saurabh Singh;Abhinav Gupta;Alexei A. Efros

  • A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection

    Xiaolong Wang;Abhinav Shrivastava;Abhinav Gupta

  • AI2-THOR: An Interactive 3D Environment for Visual AI

    Eric Kolve;Roozbeh Mottaghi;Daniel Gordon;Yuke Zhu

  • Robust adversarial reinforcement learning

    Lerrel Pinto;James Davidson;Rahul Sukthankar;Abhinav Gupta

  • What makes Paris look like Paris

    Carl Doersch;Saurabh Singh;Abhinav Gupta;Josef Sivic

Frequent Co-Authors

Xiaolong Wang
Xiaolong Wang University of California, San Diego
Larry S. Davis
Larry S. Davis University of Maryland, College Park
Abhinav Shrivastava
Abhinav Shrivastava University of Maryland, College Park
Ali Farhadi
Ali Farhadi University of Washington
Martial Hebert
Martial Hebert Carnegie Mellon University
Alexei A. Efros
Alexei A. Efros University of California, Berkeley
Xinlei Chen
Xinlei Chen Facebook (United States)
Roozbeh Mottaghi
Roozbeh Mottaghi University of Washington
Josef Sivic
Josef Sivic Czech Technical University in Prague
Michael J. Tarr
Michael J. Tarr Carnegie Mellon University

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