Chris Tensmeyer

Research Scientist

San Jose

Chris joined the Document Intelligence Lab at Adobe Research as a Research Scientist after performing a Summer research internship. He graduated with a PhD in computer science from Brigham Young University in 2019, and worked on several document analysis problems as part of his dissertation.  His research interests primarily lie at the intersection of document image analysis and deep learning with tasks such as document classification, document segmentation, and handwriting recognition.  He is also interested in deep learning models and training methods with applications in computer vision and natural language processing.  My current focus areas are table analysis, chart understanding, and handwriting recognition.

Publications

Deep Splitting and Merging for Table Structure Decomposition

Tensmeyer, C., Morariu, V., Price, B., Cohen, S., Martinez, T. (Sep. 23, 2019)

International Conference on Document Analysis and Recognition (ICDAR)

ICDAR 2019 Competition on Harvesting Raw Tables from Infographics (CHART-Infographics)

Davila, K., Kota, B., Setlur, S., Govindraju, V., Tensmeyer, C., Shekhar, S., Chaudhry, R. (Sep. 20, 2019)

2019 International Conference on Document Analysis and Recognition

Deep Visual Template-Free Form Parsing

Davis, B., Morse, B., Cohen, S., Price, B., Tensmeyer, C. (Sep. 20, 2019)

International Conference on Document Analysis and Recognition (ICDAR)