Ph.D. The University of North Carolina at Chapel Hill, 2015M.S. Stony Brook University (SUNY), 2013Eng. Escuela Superior Politécnica del Litoral, 2008
"Our group builds systems that can describe visual information using natural language and learn to do so efficiently from large amounts of data."
Vicente Ordonez-Roman, Assistant Professor
Research interests include:
Computer Vision, Machine Learning, Natural Language Processing
I'm Assistant Professor in the Department of Computer Science at the University of Virginia. I also spent a year as visiting research fellow at the Allen Institute for Artificial Intelligence (AI2) n the Computer Vision group. My research lies at the intersection of Computer Vision, Natural Language Processing and Machine Learning. I am especially interested in analyzing, and mining useful human insights from enormous amounts of images with associated text. I am also interested in big scale visual analytics by learning models that can perform high-level perceptual tasks for applications in social media, urban computing, and everyday activities. I'm a recipient of the 2013 IEEE Marr Prize in Computer Vision, Best Long Paper Award at EMNLP 2017, and Faculty Awards from Google, Facebook, and IBM.
Awards
NSF CAREER Award2021
Facebook Research Award2020
Google Faculty Research Award2017
IBM Faculty Award2017
EMNLP Best Paper Award2017
IEEE Marr Prize -- ICCV Best Paper Award2013
Yahoo Key Scientific Challenges Award2012
Research Interests
Computer Vision
Machine Learning
Natural Language Processing
Selected Publications
Face Recognition Technologies in the Wild: A Call for a Federal Office. Whitepaper. May 2020. ABSErik Learned-Miller, Vicente Ordóñez Román, Jamie Morgenstern, Joy Buolamwini
Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries. Conf. on Neural Information Processing Systems. NeurIPS 2019. Vancouver, Canada. ABSFuwen Tan, Paola Cascante-Bonilla, Xiaoxiao Guo, Hui Wu, Song Feng, Vicente Ordonez
Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations. International Conference on Computer Vision. ICCV 2019. Seoul, South Korea ABSTianlu Wang, Jieyu Zhao, Mark Yatskar, Kai-Wei Chang, Vicente Ordonez
Text2Scene: Generating Compositional Scenes from Textual Descriptions. Conference on Computer Vision and Pattern Recognition. CVPR 2019. Long Beach, California. ABSFuwen Tan, Song Feng, Vicente Ordonez
Feedback-prop: Convolutional Neural Network Inference under Partial Evidence. CVPR 2018. Salt Lake City, Utah. ABSTianlu Wang, Kota Yamaguchi, Vicente Ordonez.
Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints (Best Long Paper Award). Conference on Empirical Methods in Natural Language Processing. EMNLP 2017. Copenhagen, Denmark. ABSJieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, Kai-Wei Chang.
Commonly Uncommon: Semantic Sparsity in Situation Recognition. Intl. Conference on Computer Vision and Pattern Recognition. CVPR 2017. Honolulu, Hawaii. July 2017. ABSMark Yatskar, Vicente Ordonez, Luke Zettlemoyer Ali Farhadi.
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks. European Conference on Computer Vision. ECCV 2016. Amsterdam, The Netherlands. October 2016. ABSMohammad Rastegari, Vicente Ordonez, Joseph Redmon, Ali Farhadi.
From Large Scale Image Categorization to Entry-Level Categories (Marr Prize, Best Paper Award). IEEE International Conference on Computer Vision. ICCV 2013. Sydney, Australia. December 2013. ABSVicente Ordonez, Jia Deng, Yejin Choi, Alexander C. Berg, Tamara L. Berg.