Xianchao Yang
Papers
1
Total Citations
46
H-Index
1
About
Xianchao Yang has established himself as a key contributor to the field of computer vision, with a primary focus on advancing pedestrian detection technologies. His most-cited work, the 2020 review "Deep learning for occluded and multi‐scale pedestrian detection," has garnered 46 citations, reflecting its importance as a foundational resource for researchers tackling two of the most persistent challenges in the domain: detecting pedestrians under occlusion and across varying scales. This comprehensive survey synthesizes the rapid progress driven by deep learning, offering a critical roadmap for applications in autonomous driving, video surveillance, and robotics. By systematically categorizing and evaluating state-of-the-art methods, Yang's review has helped shape subsequent research directions, providing both newcomers and seasoned experts with a clear understanding of the field's evolution and remaining hurdles. His work underscores a commitment to solving real-world safety and automation problems, where reliable pedestrian detection is paramount. Through this synthesis, Yang has not only documented unprecedented advances but also highlighted the ongoing need for robust, multi-scale solutions, cementing his role as a thoughtful analyst and guide in this fast-moving area of computer vision.
Research Focus
Key Achievements
Top Papers
- 1Deep learning for occluded and multi‐scale pedestrian detection: A review46 citations · 2020