Sehoon Lim

TL;DR: This paper designs a Monitor-Camera Imaging System (MCIS) for easier real pair data acquisition, and a model-based data synthesizing pipeline to generate Point Spread Function (PSF) and UDC data only from display pattern and camera measurements, and resolves the complicated degradation using deconvolution-based pipeline and learning-based methods.

TL;DR: Zhang et al. as mentioned in this paper focused on a newly defined under-display camera (UDC), as a novel real-world single image restoration problem. And they designed a Monitor-Camera Imaging System (MCIS) for easier real pair data acquisition, and a model-based data synthesizing pipeline to generate Point Spread Function (PSF) and UDC data only from display pattern and camera measurements.

TL;DR: The first Under-Display Camera (UDC) image restoration challenge was held in conjunction with the RLQ workshop at ECCV 2020 as mentioned in this paper, where the challenge tracks correspond to two types of display: a 4k Transparent OLED and a phone Pentile OLED.

TL;DR: The results in the paper are state-of-the-art restoration performance of Under-Display Camera Restoration.

TL;DR: In this paper, the authors determine a position of a subject in relation to multiple cameras, selecting a foreground camera from the cameras based on at least the determined position, obtaining an RGB image captured by the foreground camera, segmenting the RGB image to identify a foreground portion corresponding to the subject, generating a foreground image from the foreground portion, and producing a composite image, including compositing the foreground image and a background image to produce a portion of the composite image.