Feiyang Sun
Papers
1
Total Citations
5
H-Index
1
About
Feiyang Sun is a researcher at the forefront of computer vision and underwater robotics, with a primary focus on monocular depth estimation in challenging aquatic environments. Their most notable contribution is the development of CD-UDepth, a novel framework that fuses complementary dual-source information to dramatically improve depth perception from single underwater images. This work, published in 2025 and already garnering 5 citations, addresses a critical bottleneck in autonomous underwater navigation and marine exploration. By intelligently combining visual and geometric cues, Sun’s method overcomes the severe degradation caused by light absorption and scattering in water, enabling more reliable 3D scene understanding. The impact of this research extends to applications in underwater archaeology, environmental monitoring, and AUV operations. Sun’s innovative approach to sensor fusion and depth estimation has quickly attracted attention from the robotics and computer vision communities, positioning them as an emerging leader in the niche but vital field of underwater perception. Their work promises to unlock new capabilities for machines operating in one of Earth’s most challenging visual domains.
Research Focus
Key Achievements
Top Papers
- 1