Ching-Chun Huang

National Yang Ming Chiao Tung University

Papers

Total Citations

H-Index

About

Ching-Chun Huang is a researcher whose work centers on computer vision and deep learning, with a particular focus on depth map processing and image disentanglement. His most notable contribution is the development of a novel method for colorizing depth maps through disentanglement, a technique that separates and enhances distinct visual features to produce more accurate and visually coherent 3D representations. This approach, detailed in his 2020 paper "Colorization of Depth Map via Disentanglement," has garnered 4 citations, reflecting its early but promising impact on the field. Huang's research addresses critical challenges in reconstructing and interpreting spatial data, with applications ranging from autonomous navigation to augmented reality. By advancing how machines perceive and render depth, he contributes to bridging the gap between raw sensor data and human-interpretable imagery. His work demonstrates a commitment to refining fundamental computer vision tasks, making him a researcher to watch for further innovations in depth-aware learning and visual disentanglement.