“Sticking Information in Plain Sight: Encoding and Detecting Hidden Stickers in the Real World” by Shatford and Rusinkiewicz
Conference:
Type(s):
Title:
- Sticking Information in Plain Sight: Encoding and Detecting Hidden Stickers in the Real World
Session/Category Title:
- Images, Video & Computer Vision
Presenter(s)/Author(s):
Abstract:
We present a pipeline for designing and detecting subtle code-conveying patterns that can be printed on transparent sticker paper, then applied to real-world surfaces, rendering the modifications imperceptible to the human eye, but robustly detectable to our model, with specific emphasis placed on allowing for human error in sticker placement.
References:
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[3] Matthew Tancik, Ben Mildenhall, and Ren Ng. 2020. StegaStamp: Invisible Hyperlinks in Physical Photographs. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2117–2126.
[4] Jingdong Wang, Ke Sun, Tianheng Cheng, Borui Jiang, Chaorui Deng, Yang Zhao, Dong Liu, Yadong Mu, Mingkui Tan, Xinggang Wang, et al. 2020. Deep High-Resolution Representation Learning for Visual Recognition. IEEE transactions on Pattern Analysis and Machine Intelligence 43, 10 (2020), 3349–3364.
[5] Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang. 2018. The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 586–595.
