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At the intersection of imaging, computer graphics, and computer vision, �鶹��Ƶ’s is pushing the boundaries of visual technology. Directed by Jinwei Ye, an associate professor in the Department of Computer Science, the lab explores every stage of the imaging pipeline—from data acquisition to 3D rendering—by designing novel algorithms, imaging systems, and immersive environments.��

The lab, which is in Van Metre Hall at �鶹��Ƶ Square, has two new standout technologies in its arsenal: the Light Stage and the Pixel Cube.��

The Light Stage—a spherical structure with around 150 LED lights pointing inward along with cameras—uses polarized, Wi-Fi-controlled lighting to create complex illumination patterns. This enables the lab to capture highly detailed 3D models of real-world objects, a capability that’s particularly useful in film, gaming, and robotics.����

“We put objects in the center and take pictures under different lighting to recover really high-quality 3D models of real physical objects,” said Yufan Zhang, a PhD student working on this project. The Light Stage was fully designed and built by Ye’s students, providing them with a unique, hands-on engineering experience.��

The Pixel Cube takes immersion a step further. Comprising 90 LED panels arranged in a cube, the system allows for panoramic simulations—perfect for applications in virtual production such as driving simulators.����

“A very intuitive application of it is immersive viewing like a VR experience without using the headset,” said Ye.��

But the lab’s ambitions stretch beyond visual hardware. Ye’s team is building a large dataset of everyday objects, intended to support generative AI development for uses ranging from entertainment to robotic training.����

“We’re creating a large 3D model dataset of diverse real-world objects, which can be used as assets either in films or in games or shown to robots,” Ye said.��

Collaboration is key to the lab’s impact, added Ye. Her team, focused on advancing computational photography and AI-integrated imaging workflows, remains committed to developing foundational tools for tomorrow’s imaging technologies. They work closely with other George �鶹��Ƶ faculty and industry partners and invite potential collaborators to reach out about interdisciplinary projects in fields such as film studies, video game development, creative visual arts, simulation, and virtual training.����

“We really want to make full use of this [equipment], so we want as many people as possible to use it,” said Ye.��

With its combination of advanced equipment, collaborative ethos, and dedication to hands-on student involvement, the Imaging and Vision Lab is making George �鶹��Ƶ a destination for next-generation research in computer vision and graphics.��

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