19 citations · 51 across the 13 of their papers we have counts for
15 papers
SupGRPO: Enhancing GRPO with Matching-based Online SFT for Text Spotting
Xudong Xie, Yuzhe Li, Jing Shi +3
Text spotting requires both accurate text recognition and precise spatial localization. Current specialised spotters excel at predicting tight bounding boxes in natural scenes, but…
Handheld Video Document Scanning: A Robust On-Device Model for Multi-Page Document Scanning
Curtis Wigington
Document capture applications on smartphones have emerged as popular tools for digitizing documents. For many individuals, capturing documents with their smartphones is more conven…
DocSynthv2: A Practical Autoregressive Modeling for Document Generation
Sanket Biswas, Rajiv Jain, Vlad I. Morariu +5
While the generation of document layouts has been extensively explored, comprehensive document generation encompassing both layout and content presents a more complex challenge. Th…
ARTIST: Improving the Generation of Text-rich Images with Disentangled Diffusion Models and Large Language Models
Jianyi Zhang, Yufan Zhou, Jiuxiang Gu +5
Diffusion models have demonstrated exceptional capabilities in generating a broad spectrum of visual content, yet their proficiency in rendering text is still limited: they often g…
Experts prefer text but videos help novices: an analysis of the utility of multi-media content
Hayeong Song, Jennifer Healey, Alexa Siu +2
Multi-media increases engagement and is increasingly prevalent in online content including news, web blogs, and social media, however, it may not always be beneficial to users. To…
Certified Neural Network Watermarks with Randomized Smoothing
Arpit Bansal, Ping-yeh Chiang, Michael Curry +5
Watermarking is a commonly used strategy to protect creators' rights to digital images, videos and audio. Recently, watermarking methods have been extended to deep learning models…
End-to-end Document Recognition and Understanding with Dessurt
Brian Davis, Bryan Morse, Bryan Price +3
We introduce Dessurt, a relatively simple document understanding transformer capable of being fine-tuned on a greater variety of document tasks than prior methods. It receives a do…
Visual FUDGE: Form Understanding via Dynamic Graph Editing
Brian Davis, Bryan Morse, Brian Price +2
We address the problem of form understanding: finding text entities and the relationships/links between them in form images. The proposed FUDGE model formulates this problem on a g…
RPCL: A Framework for Improving Cross-Domain Detection with Auxiliary Tasks
Kai Li, Curtis Wigington, Chris Tensmeyer +5
Cross-Domain Detection (XDD) aims to train an object detector using labeled image from a source domain but have good performance in the target domain with only unlabeled images. Ex…
Lets Make A Story Measuring MR Child Engagement
Duotun Wang, Jennifer Healey, Jing Qian +3
We present the result of a pilot study measuring child engagement with the Lets Make A Story system, a novel mixed reality, MR, collaborative storytelling system designed for grand…
Text and Style Conditioned GAN for Generation of Offline Handwriting Lines
Brian Davis, Chris Tensmeyer, Brian Price +3
This paper presents a GAN for generating images of handwritten lines conditioned on arbitrary text and latent style vectors. Unlike prior work, which produce stroke points or singl…
Using Behavioral Interactions from a Mobile Device to Classify the Reader's Prior Familiarity and Goal Conditions
Sungjin Nam, Zoya Bylinskii, Christopher Tensmeyer +3
A student reads a textbook to learn a new topic; an attorney leafs through familiar legal documents. Each reader may have a different goal for, and prior knowledge of, their readin…
Cross-Domain Document Object Detection: Benchmark Suite and Method
Kai Li, Curtis Wigington, Chris Tensmeyer +6
Decomposing images of document pages into high-level semantic regions (e.g., figures, tables, paragraphs), document object detection (DOD) is fundamental for downstream tasks like…
Language Model Supervision for Handwriting Recognition Model Adaptation
Chris Tensmeyer, Curtis Wigington, Brian Davis +3
Training state-of-the-art offline handwriting recognition (HWR) models requires large labeled datasets, but unfortunately such datasets are not available in all languages and domai…
PageNet: Page Boundary Extraction in Historical Handwritten Documents
Chris Tensmeyer, Brian Davis, Curtis Wigington +2
When digitizing a document into an image, it is common to include a surrounding border region to visually indicate that the entire document is present in the image. However, this b…