Due to the COVID-19 epidemic, video conferencing has evolved as a new
paradigm of communication and teamwork. However, private and personal
information can be easily leaked through cameras during video conferencing.
This includes leakage of a person’s appearance as well as the contents in the
background. This paper proposes a novel way of using online low-resolution
thermal images as conditions to guide the synthesis of RGB images, bringing a
promising solution for real-time video conferencing when privacy leakage is a
concern. SPADE-SR (Spatially-Adaptive De-normalization with Self Resampling), a
variant of SPADE, is adopted to incorporate the spatial property of a thermal
heatmap and the non-thermal property of a normal, privacy-free pre-recorded RGB
image provided in a form of latent code. We create a PAIR-LRT-Human (LRT =
Low-Resolution Thermal) dataset to validate our claims. The result enables a
convenient way of video conferencing where users no longer need to groom
themselves and tidy up backgrounds for a short meeting. Additionally, it allows
a user to switch to a different appearance and background during a conference.
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