RoPaSS: Robust Watermarking for Partial Screen-Shooting Scenarios

Authors

  • Zehua Ma Anhui Province Key Laboratory of Digital Security, University of Science and Technology of China
  • Han Fang National University of Singapore
  • Xi Yang Jinan University
  • Kejiang Chen Anhui Province Key Laboratory of Digital Security, University of Science and Technology of China
  • Weiming Zhang Anhui Province Key Laboratory of Digital Security, University of Science and Technology of China Institute of Hefei High Dimensional Data Ltd.

DOI:

https://doi.org/10.1609/aaai.v39i18.34128

Abstract

Screen-shooting robust watermarking is an effective means of preventing screen content leakage from unauthorized camera shooting, as it can trace the leaked source through the watermark extraction thereby providing an effective deterrent. However, current screen-shooting resilient watermarking schemes rely on the image's contours to synchronize and then extract the watermark. While in practical applications, it's common for only a portion of the image to be captured, resulting in a limited performance of the previous watermarking schemes. To address this problem, we propose the RoPaSS: a robust watermarking scheme for partial screen-shooting scenarios, which effectively constructs symmetric characteristics on the embedding watermark to handle the sticky re-synchronization issue. Specifically, RoPaSS consists of a watermark encoder, a decoder, and three estimators, which are trained in two stages. In the first training stage, RoPaSS integrates the flipping operation into the watermark encoder and decoder training to increase the redundancy of watermark messages and artificially guide the generation of symmetric watermarks. In the second stage, estimators utilize the watermark symmetry as an additional reference to estimate the restoration parameters to resynchronize the partially captured watermarked image. Experiments have demonstrated the excellent performance of RoPaSS in partial screen-shooting traceability, with extraction accuracy of above 93% in frontal shooting and above 86% in 30° shooting even if only 50% of the image content is captured.

Published

2025-04-11

How to Cite

Ma, Z., Fang, H., Yang, X., Chen, K., & Zhang, W. (2025). RoPaSS: Robust Watermarking for Partial Screen-Shooting Scenarios. Proceedings of the AAAI Conference on Artificial Intelligence, 39(18), 19332–19339. https://doi.org/10.1609/aaai.v39i18.34128

Issue

Section

AAAI Technical Track on Machine Learning IV