21 citations · 47 across the 10 of their papers we have counts for
11 papers
Can Foundation Models Revolutionize Mobile AR Sparse Sensing?
Yiqin Zhao, Tian Guo
Mobile sensing systems have long faced a fundamental trade-off between sensing quality and efficiency due to constraints in computation, power, and other limitations. Sparse sensin…
AR as an Evaluation Playground: Bridging Metrics and Visual Perception of Computer Vision Models
Ashkan Ganj, Yiqin Zhao, Tian Guo
Quantitative metrics are central to evaluating computer vision (CV) models, but they often fail to capture real-world performance due to protocol inconsistencies and ground-truth n…
CleAR: Robust Context-Guided Generative Lighting Estimation for Mobile Augmented Reality
Yiqin Zhao, Mallesham Dasari, Tian Guo
High-quality environment lighting is essential for creating immersive mobile augmented reality (AR) experiences. However, achieving visually coherent estimation for mobile AR is ch…
Mobile AR Depth Estimation: Challenges & Prospects -- Extended Version
Ashkan Ganj, Yiqin Zhao, Hang Su +1
Metric depth estimation plays an important role in mobile augmented reality (AR). With accurate metric depth, we can achieve more realistic user interactions such as object placeme…
Get-A-Sense: Designing Spatial Context Awareness for Mobile AR Environment Understanding
Yiqin Zhao, Ashkan Ganj, Tian Guo
Physical environment understanding is vital in delivering immersive and interactive mobile augmented reality (AR) user experiences. Recently, we have witnessed a transition in the…
Toward Scalable and Controllable AR Experimentation
Ashkan Ganj, Yiqin Zhao, Federico Galbiati +1
To understand how well a proposed augmented reality (AR) solution works, existing papers often conducted tailored and isolated evaluations for specific AR tasks, e.g., depth or lig…
LitAR: Visually Coherent Lighting for Mobile Augmented Reality
Yiqin Zhao, Chongyang Ma, Haibin Huang +1
An accurate understanding of omnidirectional environment lighting is crucial for high-quality virtual object rendering in mobile augmented reality (AR). In particular, to support r…
Multi-Camera Lighting Estimation for Photorealistic Front-Facing Mobile Augmented Reality
Yiqin Zhao, Sean Fanello, Tian Guo
Lighting understanding plays an important role in virtual object composition, including mobile augmented reality (AR) applications. Prior work often targets recovering lighting fro…
Privacy-preserving Reflection Rendering for Augmented Reality
Yiqin Zhao, Sheng Wei, Tian Guo
Many augmented reality (AR) applications rely on omnidirectional environment lighting to render photorealistic virtual objects. When the virtual objects consist of reflective mater…
Xihe: A 3D Vision-based Lighting Estimation Framework for Mobile Augmented Reality
Yiqin Zhao, Tian Guo
Omnidirectional lighting provides the foundation for achieving spatially-variant photorealistic 3D rendering, a desirable property for mobile augmented reality applications. Howeve…
PointAR: Efficient Lighting Estimation for Mobile Augmented Reality
Yiqin Zhao, Tian Guo
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 learnin…