Examples extend to methods, systems, and computer program products for disrupting object recognition functionality. Images can be altered in a manner that makes it difficult (if not impossible) for recognition algorithms to accurately recognize faces, vehicles, people, etc. in the images. Image alterations can be tailored to disrupt recognition algorithms while being imperceptible to the human eye and/or minimizing impact on other image processing systems. In some aspects, Machine Leaning (ML) frameworks and/or leaning-based generative/discriminative model techniques, such as, for example, Generative Adversarial Networks (GANs), are used to alter images.
DISRUPTING OBJECT RECOGNITION FUNCTIONALITY