Chenfei Chang

National Taiwan University of Science and Technology

Papers

Total Citations

H-Index

About

Dr. Chenfei Chang is a leading researcher in autonomous navigation and computer vision, with a primary focus on advancing visual odometry (VO) for robotics and self-driving vehicles. Their most-cited work, "Learning-Based Heatmap-Guided Model for Monocular Visual Odometry" (2025), tackles critical limitations in traditional VO systems—specifically, their fragility in dynamic lighting or low-texture environments. By integrating a heatmap-guided learning framework, Dr. Chang’s model enhances robustness and accuracy where conventional feature-based or direct methods fail. This contribution has already garnered 3 citations, signaling growing influence in the field. Dr. Chang’s research bridges deep learning and geometric estimation, offering practical solutions for real-world deployment in challenging conditions. Their work is particularly notable for its potential to improve safety and reliability in autonomous systems, from drones to self-driving cars. As a rising voice in robotics, Dr. Chang continues to push the boundaries of monocular perception, making their research essential reading for students and engineers tackling the next generation of navigation technology.