EdgeRelight360: Text-Conditioned 360-Degree HDR Image Generation for
  Real-Time On-Device Video Portrait Relighting
Min-Hui Lin Mahesh Reddy Guillaume Berger Michel Sarkis Fatih Porikli Ning Bi
In this paper, we present EdgeRelight360, an approach for real-time video
portrait relighting on mobile devices, utilizing text-conditioned generation of
360-degree high dynamic range image (HDRI) maps. Our method proposes a
diffusion-based text-to-360-degree image generation in the HDR domain, taking
advantage of the HDR10 standard. This technique facilitates the generation of
high-quality, realistic lighting conditions from textual descriptions, offering
flexibility and control in portrait video relighting task. Unlike the previous
relighting frameworks, our proposed system performs video relighting directly
on-device, enabling real-time inference with real 360-degree HDRI maps. This
on-device processing ensures both privacy and guarantees low runtime, providing
an immediate response to changes in lighting conditions or user inputs. Our
approach paves the way for new possibilities in real-time video applications,
including video conferencing, gaming, and augmented reality, by allowing
dynamic, text-based control of lighting conditions.