  Modern image processing tools have made it easy for attackers to crop the
region or object of interest in images and paste it into other images. The
challenge this cropping-paste attack poses to the watermarking technology is
that it breaks the synchronization of the image watermark, introducing multiple
superimposed desynchronization distortions, such as rotation, scaling, and
translation. However, current watermarking methods can only resist a single
type of desynchronization and cannot be applied to protect the object's
copyright under the cropping-paste attack. With the finding that the key to
resisting the cropping-paste attack lies in robust features of the object to
protect, this paper proposes a self-synchronizing object-aligned watermarking
method, called SSyncOA. Specifically, we first constrain the watermarked region
to be aligned with the protected object, and then synchronize the watermark's
translation, rotation, and scaling distortions by normalizing the object
invariant features, i.e., its centroid, principal orientation, and minimum
bounding square, respectively. To make the watermark embedded in the protected
object, we introduce the object-aligned watermarking model, which incorporates
the real cropping-paste attack into the encoder-noise layer-decoder pipeline
and is optimized end-to-end. Besides, we illustrate the effect of different
desynchronization distortions on the watermark training, which confirms the
necessity of the self-synchronization process. Extensive experiments
demonstrate the superiority of our method over other SOTAs.
