  This article presents SVC-onGoing, an on-going competition for on-line
signature verification where researchers can easily benchmark their systems
against the state of the art in an open common platform using large-scale
public databases, such as DeepSignDB and SVC2021_EvalDB, and standard
experimental protocols. SVC-onGoing is based on the ICDAR 2021 Competition on
On-Line Signature Verification (SVC 2021), which has been extended to allow
participants anytime. The goal of SVC-onGoing is to evaluate the limits of
on-line signature verification systems on popular scenarios (office/mobile) and
writing inputs (stylus/finger) through large-scale public databases. Three
different tasks are considered in the competition, simulating realistic
scenarios as both random and skilled forgeries are simultaneously considered on
each task. The results obtained in SVC-onGoing prove the high potential of deep
learning methods in comparison with traditional methods. In particular, the
best signature verification system has obtained Equal Error Rate (EER) values
of 3.33% (Task 1), 7.41% (Task 2), and 6.04% (Task 3). Future studies in the
field should be oriented to improve the performance of signature verification
systems on the challenging mobile scenarios of SVC-onGoing in which several
mobile devices and the finger are used during the signature acquisition.
