Licheng Jiao
Papers
5
Total Citations
50
H-Index
4
About
Licheng Jiao is a researcher whose work spans computer vision, robotics, and intelligent systems, with a particular focus on semantic segmentation and autonomous perception. His most cited paper, "AttAN: Attention Adversarial Networks for 3D Point Cloud Semantic Segmentation" (2020, 19 citations), addresses a critical limitation in 3D scene understanding—the independent prediction of points—by introducing attention mechanisms and adversarial training to improve segmentation continuity for applications like autonomous driving and AR/VR. Jiao also contributed to real-time image segmentation with his 2024 work on a Multiple Resolutions Detail Enhancement Network, designed to preserve low-level spatial information for fast, interactive tasks such as robot control. In robotics, he has explored the kinematics and dynamics of specialized systems, including a novel friction stir welding robot and a 3-RPS parallel robot, using multi-software co-simulation to model rigid-flexible coupling. His work on gigapixel-level pedestrian detection (2021, 12 citations) further demonstrates his interest in scaling vision algorithms for high-resolution, real-world scenarios. With a growing citation record and contributions that bridge deep learning and mechanical design, Jiao is advancing the capabilities of autonomous systems and intelligent robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5