  Under Display Cameras present a promising opportunity for phone manufacturers
to achieve bezel-free displays by positioning the camera behind
semi-transparent OLED screens. Unfortunately, such imaging systems suffer from
severe image degradation due to light attenuation and diffraction effects. In
this work, we present Deep Atrous Guided Filter (DAGF), a two-stage, end-to-end
approach for image restoration in UDC systems. A Low-Resolution Network first
restores image quality at low-resolution, which is subsequently used by the
Guided Filter Network as a filtering input to produce a high-resolution output.
Besides the initial downsampling, our low-resolution network uses multiple,
parallel atrous convolutions to preserve spatial resolution and emulates
multi-scale processing. Our approach's ability to directly train on megapixel
images results in significant performance improvement. We additionally propose
a simple simulation scheme to pre-train our model and boost performance. Our
overall framework ranks 2nd and 5th in the RLQ-TOD'20 UDC Challenge for POLED
and TOLED displays, respectively.
