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About

Qianhui Sun is a rising researcher in computer vision and robotics, whose work centers on depth perception and multimodal sensor fusion. Her most notable contribution comes from the MIPI 2023 Challenge on RGB+ToF Depth Completion, where she helped advance methods for reconstructing dense depth maps from sparse Time-of-Flight measurements combined with RGB images. This challenge addressed a critical bottleneck in real-world applications—how to achieve accurate depth sensing under low-light or textureless conditions where traditional stereo or structured light approaches fail. By organizing and benchmarking state-of-the-art deep learning solutions, Sun’s work has directly influenced the development of more robust perception systems for autonomous navigation and augmented reality. Though early in her career, her research has already garnered attention, with her leading paper accumulating 6 citations and serving as a reference point for subsequent depth completion studies. Her contributions highlight a commitment to solving practical sensor fusion problems, bridging the gap between sparse, noisy hardware data and the high-resolution depth maps needed for reliable scene understanding.