Sai Bi

Papers

Total Citations

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About

Sai Bi is a leading researcher in computer vision and graphics, with a primary focus on photorealistic scene reconstruction, inverse rendering, and data-driven methods for indoor environments. His most impactful contribution is the **OpenRooms** framework, which revolutionized the creation of large-scale, photorealistic indoor scene datasets. By transforming raw 3D scans into richly annotated data with ground truth geometry, material, lighting, and semantics, Bi’s work makes high-quality dataset generation widely accessible—a critical enabler for training deep learning models in scene understanding and rendering. The flagship paper, “OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets” (2021), has garnered **66 citations**, underscoring its influence. A follow-up end-to-end version (2020) further refined the pipeline, earning **13 citations**. Bi’s contributions bridge the gap between synthetic and real-world data, empowering researchers to tackle complex tasks like relighting, material estimation, and semantic segmentation. His work is a cornerstone for advancing photorealistic simulation in augmented reality, robotics, and computer graphics, making him a key figure in democratizing high-fidelity scene data.