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Found 5 papers, 3 papers with code
Mobile AR Depth Estimation: Challenges & Prospects -- Extended Version
In this paper, we investigate the challenges and opportunities of achieving accurate metric depth estimation in mobile AR.
LitAR: Visually Coherent Lighting for Mobile Augmented Reality
In this work, we present the design and implementation of a lighting reconstruction framework called LitAR that enables realistic and visually-coherent rendering.
Multi-Camera Lighting Estimation for Photorealistic Front-Facing Mobile Augmented Reality
This lack of support can be attributed to the unique challenges of obtaining 360$^\circ$ HDR environment maps, an ideal format of lighting representation, from the front-facing camera and existing techniques.
Xihe: A 3D Vision-based Lighting Estimation Framework for Mobile Augmented Reality
Centering the key idea of 3D vision, in this work, we design an edge-assisted framework called Xihe to provide mobile AR applications the ability to obtain accurate omnidirectional lighting estimation in real time.
PointAR: Efficient Lighting Estimation for Mobile Augmented Reality
We propose an efficient lighting estimation pipeline that is suitable to run on modern mobile devices, with comparable resource complexities to state-of-the-art mobile deep learning models.
