Respectful cameras: detecting visual markers in real-time to address privacy concerns

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

NoPeek: Information leakage reduction to share activations in distributed deep learning (2020, background): “[1, 2, 3, 4, 5, 2, 6, 7, 8, 9].”
Privacy in Deep Learning: A Survey (2020, background): “This poses serious privacy concerns, as neural networks are used in different aspects of our lives [5, 3, 6, 7, 8, 9, 10].”
World-Driven Access Control for Continuous Sensing (2014, background): “We believe that the foundations laid herein will facilitate further work in the ﬁeld.”
What You Mark is What Apps See (2016, background): “As with least privilege, these systems require designers to anticipate a large universe of objects, which vision algorithms must detect and block.”
MarkIt: privacy markers for protecting visual secrets (2014, methodology): “[17] using color based visual markers to detect and block faces.”
In situ with bystanders of augmented reality glasses: perspectives on recording and privacy-mediating technologies (2014, background): “, [29]) if they do not wish to be recorded.”