Chris Thomas at Virginia Tech

378 Data and Decision Sciences Building

727 Prices Fork Rd

Blacksburg, VA 24060

(540) 231-2993

I am an Assistant Professor in the Department of Computer Science at Virginia Tech. My research is in computer vision. I am interested in many problems requiring reasoning across multimodal data, such as cross-modal retrieval, high-level content understanding, and multimodal knowledge representation. I am associated with the Sanghani Center for Artificial Intelligence and Data Analytics.

Prior to joining Virginia Tech, I was a postdoctoral researcher at Columbia University working with Professor Shih-Fu Chang. I received my Ph.D. in Computer Science from the Department of Computer Science at the University of Pittsburgh in 2020. My advisor was Professor Adriana Kovashka.

Note: I am currently recruiting strong and motivated students to join our growing group! Please visit the Prospective Students page for details.

Recent News

Jul 2022	Our paper on fine-grained visual entailment was accepted to ECCV 2022
Jun 2022	Our journal article on using weak caption supervision for object detection was accepted to the IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)
Aug 2021	Awarded ICCV 2021 Outstanding Reviewer
Jun 2021	Our journal article on predicting visual political bias was accepted to the International Journal of Computer Vision
May 2021	Our paper on fine-grained cross-modal consistency checking for fake news detection was accepted as an oral to ACL 2021
May 2021	Awarded CVPR 2021 Outstanding Reviewer

Selected Publications

Fine-Grained Visual Entailment

Christopher Thomas, Yipeng Zhang, and Shih-Fu Chang

In Proceedings of the European Conference on Computer Vision, 2022

arXiv Bib HTML

@inproceedings{thomas2022fine,
  title = {Fine-Grained Visual Entailment},
  author = {Thomas, Christopher and Zhang, Yipeng and Chang, Shih-Fu},
  booktitle = {Proceedings of the European Conference on Computer Vision},
  pages = {398--416},
  year = {2022},
}

InfoSurgeon: Cross-Media Fine-grained Information Consistency Checking for Fake News Detection

Yi Fung, Christopher Thomas, Revanth Reddy, and 6 more authors

In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL), 2021

Bib HTML

@inproceedings{fung2021infosurgeon,
  title = {InfoSurgeon: Cross-Media Fine-grained Information Consistency Checking for Fake News Detection},
  author = {Fung, Yi and Thomas, Christopher and Reddy, Revanth and Polisetty, Sandeep and Ji, Heng and Chang, Shih-Fu and McKeown, Kathleen and Bansal, Mohit and Sil, Avi},
  booktitle = {Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL)},
  year = {2021},
}

Preserving Semantic Neighborhoods for Robust Cross-modal Retrieval

Christopher Thomas, and Adriana Kovashka

In Proceedings of the European Conference on Computer Vision (ECCV), 2020

Bib HTML PDF Website

@inproceedings{thomas2020preserving,
  title = {Preserving Semantic Neighborhoods for Robust Cross-modal Retrieval},
  author = {Thomas, Christopher and Kovashka, Adriana},
  booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
  year = {2020},
}

Predicting the politics of an image using webly supervised data

Christopher Thomas, and Adriana Kovashka

In Advances in Neural Information Processing Systems (NeurIPS 2019), 2019

Bib PDF Supp Poster Slides Website

@inproceedings{thomas2019predicting,
  title = {Predicting the politics of an image using webly supervised data},
  author = {Thomas, Christopher and Kovashka, Adriana},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS 2019)},
  year = {2019},
}