Imprinto: Enhancing Infrared Inkjet Watermarking for Human and Machine Perception
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Abstract (arXiv)
Hybrid paper interfaces leverage augmented reality to combine the desired tangibility of paper documents with the affordances of interactive digital media. Typically, virtual content can be embedded through direct links (e.g., QR codes); however, this impacts the aesthetics of the paper print and limits the available visual content space. To address this problem, we present Imprinto, an infrared inkjet watermarking technique that allows for invisible content embeddings only by using off-the-shelf IR inks and a camera. Imprinto was established through a psychophysical experiment, studying how much IR ink can be used while remaining invisible to users regardless of background color. We demonstrate that we can detect invisible IR content through our machine learning pipeline, and we developed an authoring tool that optimizes the amount of IR ink on the color regions of an input document for machine and human detectability. Finally, we demonstrate several applications, including augmenting paper documents and objects.
Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 16 of its 85 references that are in the map. First posted on arXiv 24 Feb 2025.
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References · 16
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- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,223
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,656
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- 2020fastai: A Layered API for Deep Learningcited by 183
- 2024Augmented Object Intelligence with XR-Objectscited by 12
- 2020VisCode: Embedding Information in Visualization Images using Encoder-Decoder Networkcited by 11
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- 2023Augmenting Static Visualizations with PapARVis Designercited by 5
- 2017FontCode: Embedding Information in Text Documents using Glyph Perturbationcited by 2
4 more
- 2018AniCode: Authoring Coded Artifacts for Network-Free Personalized Animationscited by 1
- 2024Ubiquitous Metadata: Design and Fabrication of Embedded Markers for Real-World Object Identification and Interactioncited by 1
- 2025XR-penter: Material-Aware and In Situ Design of Scrap Wood Assembliescited by 1
- 2025Draw2Cut: Direct On-Material Annotations for CNC Millingcited by 1
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- 2025Watermarking for AI Content Detection: A Review on Text, Visual, and Audio Modalities
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- 2025Secure and Robust Watermarking for AI-generated Images: A Comprehensive Survey
- 2025Towards Imperceptible Watermarking Via Environment Illumination for Consumer Cameras
- 2024InvisMark: Invisible and Robust Watermarking for AI-generated Image Provenance