Haotian Qian

Papers

Total Citations

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About

Haotian Qian is a rising researcher in computer vision, with a primary focus on underwater image enhancement—a critical area for advancing autonomous underwater robotics and marine exploration. His most cited work, the "Structure-Inferred Bi-level Model for Underwater Image Enhancement" (2022), tackles the persistent challenges of color cast and low visibility caused by light scattering and absorption in water. This innovative bi-level framework not only restores image clarity but also preserves structural integrity, setting a new benchmark for quality in degraded underwater scenes. With 19 citations in just a short time, the paper signals growing recognition of his contributions. Qian’s research bridges the gap between theoretical modeling and practical deployment, offering robust solutions for real-world applications in oceanography and underwater inspection. His work is particularly notable for its dual focus on physical degradation modeling and data-driven enhancement, demonstrating a sophisticated understanding of both optics and deep learning. As the field of underwater vision expands, Haotian Qian’s early achievements position him as a promising voice in making the deep sea visible to machines.