World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
16697
World Ranking
7380
National Ranking
3216

Overview

Jason J. Corso is affiliated with the University of Michigan-Ann Arbor in the United States. Their research primarily falls within the broad field of Computer Science, with a particular focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Surgery, Cardiology and Cardiovascular Medicine, and Control and Systems Engineering.

Their work covers a range of specialized topics including:

  • Human Pose and Action Recognition
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications
  • Generative Adversarial Networks and Image Synthesis

Jason J. Corso has contributed to various publication venues. The most frequent of these include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Surgery
  • IEEE Transactions on Neural Networks and Learning Systems
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Some recent papers include:

  • Unified Vision-Language Pre-Training for Image Captioning and VQA, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation, 2020, arXiv (Cornell University)
  • The impact of team familiarity on intra and postoperative cardiac surgical outcomes, 2021, Surgery
  • Slimming Neural Networks Using Adaptive Connectivity Scores, 2022, IEEE Transactions on Neural Networks and Learning Systems
  • The DEVIL is in the Details: A Diagnostic Evaluation Benchmark for Video Inpainting, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Frequent collaborators of Jason J. Corso include Nathan Louis, Steven Yule, Roger D. Dias, Milisa Manojlovich, and Francis D. Pagani. These coauthors have contributed multiple times to research projects alongside Corso.

Best Publications

  • The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

    Bjoern H. Menze;Andras Jakab;Stefan Bauer;Jayashree Kalpathy-Cramer

  • Action bank: A high-level representation of activity in video

    Sreemanananth Sadanand;Jason J. Corso

  • Unified Vision-Language Pre-Training for Image Captioning and VQA

    Luowei Zhou;Hamid Palangi;Lei Zhang;Houdong Hu

  • Efficient Multilevel Brain Tumor Segmentation With Integrated Bayesian Model Classification

    J.J. Corso;E. Sharon;S. Dube;S. El-Saden

  • End-to-End Dense Video Captioning with Masked Transformer

    Luowei Zhou;Yingbo Zhou;Jason J. Corso;Richard Socher

  • Towards Automatic Learning of Procedures from Web Instructional Videos

    Luowei Zhou;Chenliang Xu;Jason J. Corso

  • Jointly modeling deep video and compositional text to bridge vision and language in a unified framework

    Ran Xu;Caiming Xiong;Wei Chen;Jason J. Corso

  • A Thousand Frames in Just a Few Words: Lingual Description of Videos through Latent Topics and Sparse Object Stitching

    Pradipto Das;Chenliang Xu;Richard F. Doell;Jason J. Corso

  • Streaming hierarchical video segmentation

    Chenliang Xu;Caiming Xiong;Jason J. Corso

  • Evaluation of super-voxel methods for early video processing

    Chenliang Xu;Jason J. Corso

  • Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection

    Duygu Sarikaya;Jason J. Corso;Khurshid A. Guru

  • Towards Automatic Learning of Procedures From Web Instructional Videos

    Luowei Zhou;Chenliang Xu;Jason J. Corso

  • Multi-Channel Attention Selection GAN With Cascaded Semantic Guidance for Cross-View Image Translation

    Hao Tang;Dan Xu;Nicu Sebe;Yanzhi Wang

  • Grounded Video Description

    Luowei Zhou;Yannis Kalantidis;Xinlei Chen;Jason J. Corso

  • Brain tumor detection and segmentation in a CRF (conditional random fields) framework with pixel-pairwise affinity and superpixel-level features.

    Wei Wu;Wei Wu;Albert Y. C. Chen;Liang Zhao;Jason J. Corso

  • TASED-Net: Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency Detection

    Kyle Min;Jason Corso

  • Stereo-Based Endoscopic Tracking of Cardiac Surface Deformation

    William W. Lau;Nicholas A. Ramey;Jason J. Corso;Nitish V. Thakor

  • Navigating inner space: 3-D assistance for minimally invasive surgery

    Darius Burschka;Jason J. Corso;Maneesh Dewan;William W. Lau

  • GPU-based cone beam computed tomography

    Peter B. Noël;Alan M. Walczak;Jinhui Xu;Jason J. Corso

  • Can humans fly? Action understanding with multiple classes of actors

    Chenliang Xu;Shao-Hang Hsieh;Caiming Xiong;Jason J. Corso

  • Labeling of Lumbar Discs Using Both Pixel- and Object-Level Features With a Two-Level Probabilistic Model

    R S Alomari;J J Corso;V Chaudhary

Frequent Co-Authors

Caiming Xiong
Caiming Xiong Salesforce (United States)
Gregory D. Hager
Gregory D. Hager Johns Hopkins University
Alan L. Yuille
Alan L. Yuille Johns Hopkins University
Yan Yan
Yan Yan Illinois Institute of Technology
Vipin Chaudhary
Vipin Chaudhary University at Buffalo, State University of New York
Zhuowen Tu
Zhuowen Tu University of California, San Diego
Nicu Sebe
Nicu Sebe University of Trento
Greg Mori
Greg Mori Simon Fraser University
Venu Govindaraju
Venu Govindaraju University at Buffalo, State University of New York
Arthur W. Toga
Arthur W. Toga University of Southern California

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