Pixel Privacy: Increasing Image Appeal while Blocking Automatic Inference of Sensitive Scene Information

Martha A. Larson, Zhuoran Liu, Simon Brugman, Zhengyu Zhao
2018 MediaEval Benchmarking Initiative for Multimedia Evaluation  
We introduce a new privacy task focused on images that users share online. The task benchmarks image transformation algorithms that are capable of blocking the ability of automatic classifiers to infer sensitive information in images. At the same time, the image transformations should maintain the original value of the image to the user who is sharing it, either by leaving it not obviously changed, or by enhancing it to increase its visual appeal. This year, the focus is on a set of 60 scene
more » ... egories, selected from the Places365-Standard dataset, that can be considered privacy-sensitive.
dblp:conf/mediaeval/LarsonLBZ18 fatcat:xgl6zurmuvgangi4jutxqjbs4u