  In an era of increasing privacy concerns for our online presence, we propose
that the decision to appear in a piece of content should only belong to the
owner of the body. Although some automatic approaches for full-body
anonymization have been proposed, human-guided anonymization can adapt to
various contexts, such as cultural norms, personal relations, esthetic
concerns, and security issues. ''My Body My Choice'' (MBMC) enables physical
and adversarial anonymization by removal and swapping approaches aimed for four
tasks, designed by single or multi, ControlNet or GAN modules, combining
several diffusion models. We evaluate anonymization on seven datasets; compare
with SOTA inpainting and anonymization methods; evaluate by image, adversarial,
and generative metrics; and conduct reidentification experiments.
