Chris Tensmeyer

Chris joined Adobe Research in 2018 as a Research Scientist after performing a Summer research internship. He graduated with a PhD in computer science from Brigham Young University and developed new deep learning models to solve document analysis problems as part of his dissertation. His research interests span a variety of document intelligence topics, including layout analysis and generation, HCI for document consumption, text recognition, and semantic understanding of documents. If you have interest in any of these topics or adjacent ones, please feel free to reach out!

Scholar Profile

Computer Vision, Imaging & Video Document Intelligence Natural Language Processing

Publications

June 3, 2026 Conference on Computer Vision and Pattern Recognition (CVPR 2026)

AnyDoc: Enhancing Document Generation via Large-Scale HTML/CSS Data Synthesis and Height-Aware Reinforcement Optimization

Jiawei Lin, Wanrong Zhu, Vlad Morariu, Chris Tensmeyer

AI & Machine Learning Content Intelligence Document Intelligence

September 2, 2024 2024 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)

FlexDoc: Flexible Document Adaptation through Optimizing both Content and Layout

Yue Jiang, Christof Lutteroth, Rajiv Jain, Chris Tensmeyer, Varun Manjunatha, Wolfgang Stuerzlinger, Vlad Morariu

Document Intelligence Human Computer Interaction

April 26, 2024 ArXiv

DocumentCLIP: Linking Figures and Main Body Text in Reflowed Documents

Fuxiao Liu, Hao Tan, Chris Tensmeyer

Document Intelligence

December 1, 2023 Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Learning the Visualness of Text Using Large Vision-Language Models

Gaurav Verma, Ryan A. Rossi, Chris Tensmeyer, Jiuxiang Gu, Ani Nenkova

Document Intelligence Natural Language Processing

October 3, 2023 2023 IEEE Symposium on Visual Languages and Human-Centric Computing

DocDancer: Authoring Ultra-responsive Documents with Layout Generation

Yuexi Chen, Leo Zhicheng Liu, Chris Tensmeyer, Niklas Elmqvist, Vlad Morariu

Document Intelligence Human Computer Interaction

June 18, 2023 Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops

Improving Cross-Domain Detection with Self-Supervised Learning

Kai Li, Curtis Wigington, Chris Tensmeyer, Vlad Morariu, Handong Zhao, Varun Manjunatha, Nikolaos Barmpalios, Yun Fu

Computer Vision, Imaging & Video Document Intelligence

April 30, 2023 Proceedings of the ACM Web Conference 2023

Web Table Formatting Affects Readability on Mobile Devices

Chris Tensmeyer, Zoya Bylinskii, Tianyuan Cai, Dave Miller, Ani Nenkova, Aleena Gertrudes Niklaus, Shaun Wallace

Document Intelligence Human Computer Interaction

December 1, 2022 Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

MGDoc: Pre-training with Multi-granular Hierarchy for Document Image Understanding

Zilong Wang, Jiuxiang Gu, Chris Tensmeyer, Nikolaos Barmpalios, Ani Nenkova, Tong Sun, Jingbo Shang, Vlad Morariu

Computer Vision, Imaging & Video Document Intelligence

November 1, 2022 Proceedings of the first Workshop on Information Extraction from Scientific Publications

TELIN: Table Entity LINker for Extracting Leaderboards from Machine Learning Publications

Sean Yang, Chris Tensmeyer, Curtis Wigington

Document Intelligence Natural Language Processing

October 23, 2022 TiE: Text in Everything (ECCV 2022 Workshop)

End-to-end Document Recognition and Understanding with Dessurt

Brian Davis, Bryan Morse, Chris Tensmeyer, Brian Price, Curtis Wigington, Vlad Morariu

Document Intelligence

June 28, 2022 Proceedings of the AAAI Conference on Artificial Intelligence

TiGAN: Text-Based Interactive Image Generation and Manipulation

Yufan Zhou, Ruiyi Zhang, Jiuxiang Gu, Chris Tensmeyer, Tong Yu, Changyou Chen, Jinhui Xu, Tong Sun

Computer Vision, Imaging & Video Natural Language Processing

June 19, 2022 Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Towards Language-Free Training for Text-to-Image Generation

Yufan Zhou, Ruiyi Zhang, Changyou Chen, Chunyuan Li, Chris Tensmeyer, Tong Yu, Jiuxiang Gu, Jinhui Xu, Tong Sun

Computer Vision, Imaging & Video Natural Language Processing

September 8, 2021 ICDAR 2021

Visual FUDGE: Form Understanding via Dynamic Graph Editing

Brian Davis, Bryan Morse, Brian Price, Chris Tensmeyer, Curtis Wigington

Document Intelligence

February 21, 2021 ICPR 2021

ICPR 2020 – Competition on Harvesting Raw Tables from Infographics

Chris Tensmeyer, Sumit Shekhar, Hrituraj Singh, Kenny Davila, Srirangaraj Setlur, Venu Govindaraju

AI & Machine Learning Document Intelligence

September 7, 2020 British Machine Vision Conference (BMVC)

Text and Style Conditioned GAN for Generation of Offline Handwriting Lines

Brian Davis, Chris Tensmeyer, Brian Price, Curtis Wigington, Bryan Morse, Rajiv Jain

AI & Machine Learning Computer Vision, Imaging & Video

June 22, 2020 Conference on Computer Vision and Pattern Recognition (CVPR)

Cross-Domain Document Object Detection: Benchmark Suite and Method

Kai Li, Curtis Wigington, Chris Tensmeyer, Handong Zhao, Nikolaos Barmpalios, Vlad Morariu, Varun Manjunatha, Tong Sun, Yun Fu

AI & Machine Learning Computer Vision, Imaging & Video Document Intelligence

May 16, 2020 Springer Nature Computer Science

Historical Document Image Binarization – A Review

Chris Tensmeyer, Tony Martinez

Computer Vision, Imaging & Video Document Intelligence

November 11, 2019 International Conference on Document Analysis and Recognition (ICDAR)

Generating Realistic Binarization Data with Generative Adversarial Networks

Chris Tensmeyer, Mike Brodie, Daniel Saunders, Tony Martinez

AI & Machine Learning Computer Vision, Imaging & Video Document Intelligence

November 11, 2019 International Conference on Document Analysis and Recognition (ICDAR)

Training Full-Page Handwritten Text Recognition Models without Annotated Line Breaks

Chris Tensmeyer, Curtis Wigington

Oral

AI & Machine Learning Computer Vision, Imaging & Video Document Intelligence

November 9, 2019 Workshop on Machine Learning (WML) at International Conference on Document Analysis and Recognition (ICDAR)

Robust Keypoint Regression

Chris Tensmeyer, Tony Martinez

Long Oral

AI & Machine Learning Computer Vision, Imaging & Video Document Intelligence

September 23, 2019 International Conference on Document Analysis and Recognition (ICDAR)

Deep Splitting and Merging for Table Structure Decomposition

Chris Tensmeyer, Vlad Morariu, Brian Price, Scott Cohen, Tony Martinez

Oral

AI & Machine Learning Computer Vision, Imaging & Video Document Intelligence

September 20, 2019 International Conference on Document Analysis and Recognition (ICDAR)

Deep Visual Template-Free Form Parsing

Brian Davis, Bryan Morse, Scott Cohen, Brian Price, Chris Tensmeyer

Oral

AI & Machine Learning Computer Vision, Imaging & Video Document Intelligence

September 20, 2019 2019 International Conference on Document Analysis and Recognition

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

Kenny Davila, Bhargava Urala Kota, Srirangraj Setlur, Venu Govindraju, Chris Tensmeyer, Sumit Shekhar, Ritwick Chaudhry

Computer Vision, Imaging & Video

September 8, 2018 European Conference on Computer Vision 2018

Start, Follow, Read: End-to-End Full-Page Handwriting Recognition

Curtis Wigington, Chris Tensmeyer, Brian Davis, Bill Barrett, Brian Price, Scott Cohen

AI & Machine Learning Computer Vision, Imaging & Video Document Intelligence

August 1, 2018 International Conference on Frontiers in Handwriting Recognition

Language Model Supervision for Handwriting Recognition Model Adaptation

Chris Tensmeyer, Curtis Wigington, Brian Davis, Seth Stewart, Tony Martinez, William Barrett

AI & Machine Learning Computer Vision, Imaging & Video Document Intelligence

September 10, 2017 International Workshop on Historical Document Imaging and Processing

PageNet: Page Boundary Extraction in Historical Handwritten Documents

Chris Tensmeyer, Brian Davis, Curtis Wigington, Iain Lee, William Barrett

AI & Machine Learning Computer Vision, Imaging & Video Document Intelligence