  During the COVID-19 pandemic, most of the human-to-human interactions have
been stopped. To mitigate the spread of deadly coronavirus, many offices took
the initiative so that the employees can work from home. But, tracking the
employees and finding out if they are really performing what they were supposed
to turn out to be a serious challenge for all the companies and organizations
who are facilitating "Work From Home". To deal with the challenge effectively,
we came up with a solution to track the employees with face recognition. We
have been testing this system experimentally for our office. To train the face
recognition module, we used FaceNet with KNN using the Labeled Faces in the
Wild (LFW) dataset and achieved 97.8\% accuracy. We integrated the trained
model into our central system, where the employees log their time. In this
paper, we discuss in brief the system we have been experimenting with and the
pros and cons of the system.
