Xiaojun Tong

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About

Xiaojun Tong is a computer vision researcher whose work centers on three-dimensional object reconstruction from stereo imagery. In a field increasingly driven by autonomous systems and immersive media, Tong’s contributions address a fundamental challenge: how to recover accurate 3D geometry from pairs of 2D images. Their most-cited paper, “Toward 3D object reconstruction from stereo images” (2021), has garnered 19 citations, establishing a foundation for subsequent work in depth estimation and scene understanding. This research advances the practical deployment of stereo vision in robotics, augmented reality, and digital twin creation, where precise spatial mapping is critical. By refining algorithms that bridge the gap between traditional photogrammetry and modern deep learning, Tong has helped push the boundaries of what can be achieved with limited input data. Their work is notable for its clarity in addressing occlusion and texture-poor regions—common stumbling blocks in real-world applications. For students and researchers exploring 3D vision, Tong’s contributions offer a clear, methodical path from stereo correspondence to robust object reconstruction, making them a valuable reference in this rapidly evolving domain.