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Computer Science

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37412
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Research.com Recognitions

  • 2018 - IEEE Fellow For contributions to video understanding

Overview

Rahul Sukthankar is affiliated with Google in the United States and has contributed extensively to the fields of computer science and engineering. Their work primarily focuses on computer vision and pattern recognition, with additional research in control and systems engineering and artificial intelligence.

Their main research topics include:

  • Human Pose and Action Recognition
  • Advanced Vision and Imaging
  • Human Motion and Animation
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Visual Attention and Saliency Detection
  • Multimodal Machine Learning Applications

Recent significant publications by Rahul Sukthankar cover various aspects of video understanding, pose estimation, and vision transformer techniques. Notable papers include:

  • Learning Video Representations from Textual Web Supervision, 2020, arXiv (Cornell University)
  • Weakly Supervised 3D Human Pose and Shape Reconstruction with Normalizing Flows, 2020, Lecture Notes in Computer Science
  • The End-of-End-to-End: A Video Understanding Pentathlon Challenge, 2020, arXiv (Cornell University)
  • Discrete Representations Strengthen Vision Transformer Robustness, 2021, arXiv (Cornell University)
  • HSPACE: Synthetic Parametric Humans Animated in Complex Environments, 2021, arXiv (Cornell University)

Frequent collaborators in their research include:

  • Andrei Zanfir
  • Eduard Gabriel Băzăvan
  • Cristian Sminchisescu
  • Marius Leordeanu
  • Dragoş Costea

Their publications are often found in venues such as:

  • arXiv (Cornell University)
  • Lecture Notes in Computer Science
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2022 International Conference on Robotics and Automation (ICRA)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

In recognition of their contributions to video understanding, Rahul Sukthankar was named an IEEE Fellow in 2018.

Best Publications

  • Large-Scale Video Classification with Convolutional Neural Networks

    Andrej Karpathy;George Toderici;Sanketh Shetty;Thomas Leung

  • PCA-SIFT: a more distinctive representation for local image descriptors

    Yan Ke;R. Sukthankar

  • Large-scale Video Classification with Convolutional Neural Networks

    Andrej Karpathy;George Toderici;Sanketh Shetty;Thomas Leung

  • AVA: A Video Dataset of Spatio-Temporally Localized Atomic Visual Actions

    Chunhui Gu;Chen Sun;David A. Ross;Carl Vondrick

  • MatchNet: Unifying feature and metric learning for patch-based matching

    Xufeng Han;Thomas Leung;Yangqing Jia;Rahul Sukthankar

  • Efficient visual event detection using volumetric features

    Yan Ke;R. Sukthankar;M. Hebert

  • Rethinking the Faster R-CNN Architecture for Temporal Action Localization

    Yu-Wei Chao;Sudheendra Vijayanarasimhan;Bryan Seybold;David A. Ross

  • Cognitive Mapping and Planning for Visual Navigation

    Saurabh Gupta;James Davidson;Sergey Levine;Rahul Sukthankar

  • Violence detection in video using computer vision techniques

    Enrique Bermejo Nievas;Oscar Deniz Suarez;Gloria Bueno García;Rahul Sukthankar

  • The THUMOS challenge on action recognition for videos “in the wild”

    Haroon Idrees;Amir Roshan Zamir;Yu-Gang Jiang;Alex Gorban

  • Event Detection in Crowded Videos

    Yan Ke;R. Sukthankar;M. Hebert

  • Brief paper: Decentralized estimation and control of graph connectivity for mobile sensor networks

    P. Yang;R. A. Freeman;G. J. Gordon;K. M. Lynch

  • Robust adversarial reinforcement learning

    Lerrel Pinto;James Davidson;Rahul Sukthankar;Abhinav Gupta

  • SfM-Net: Learning of Structure and Motion from Video

    Sudheendra Vijayanarasimhan;Susanna Ricco;Cordelia Schmid;Rahul Sukthankar

  • Smarter presentations: exploiting homography in camera-projector systems

    R. Sukthankar;R.G. Stockton;M.D. Mullin

  • Beyond Skip Connections: Top-Down Modulation for Object Detection

    Abhinav Shrivastava;Rahul Sukthankar;Jitendra Malik;Abhinav Gupta

  • Variable Rate Image Compression with Recurrent Neural Networks

    George Toderici;Sean M. O'Malley;Sung Jin Hwang;Damien Vincent

  • An Integer Projected Fixed Point Method for Graph Matching and MAP Inference

    Marius Leordeanu;Martial Hebert;Rahul Sukthankar

  • An efficient parts-based near-duplicate and sub-image retrieval system

    Yan Ke;Rahul Sukthankar;Larry Huston

  • A framework for photo-quality assessment and enhancement based on visual aesthetics

    Subhabrata Bhattacharya;Rahul Sukthankar;Mubarak Shah

  • Cognitive Mapping and Planning for Visual Navigation

    Saurabh Gupta;Saurabh Gupta;Varun Tolani;James Davidson;Sergey Levine;Sergey Levine

Frequent Co-Authors

Martial Hebert
Martial Hebert Carnegie Mellon University
Shumeet Baluja
Shumeet Baluja Google (United States)
Chen Sun
Chen Sun Google (United States)
Mubarak Shah
Mubarak Shah University of Central Florida
Marius Leordeanu
Marius Leordeanu Romanian Academy
Rong Jin
Rong Jin Alibaba Group (China)
Jitendra Malik
Jitendra Malik University of California, Berkeley
Charles E. Thorpe
Charles E. Thorpe Carnegie Mellon University
Mahadev Satyanarayanan
Mahadev Satyanarayanan Carnegie Mellon University

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