Shaoxiang Guo
Papers
1
Total Citations
8
H-Index
1
About
Dr. Shaoxiang Guo is a researcher at the forefront of computer vision and intelligent material perception, with a specialized focus on the automatic detection and identification of transmittance surfaces. His work addresses a critical gap in robotics and industrial automation: enabling machines to reliably recognize transparent and translucent materials like glass and plastic from visual data. Guo’s most cited paper, “Transmittance Surface Detection and Material Identification Using Multitask ViT-SIFT Fusion” (2022, 8 citations), introduces a pioneering multitask learning framework that synergizes Vision Transformers (ViT) with SIFT features. This fusion approach significantly enhances both the detection of transmittance surfaces and the classification of their material type, overcoming challenges that traditional methods struggle with due to the ambiguous visual properties of such surfaces. By tackling this fundamental problem, Guo’s contributions have direct implications for domestic service robotics, where safe handling of fragile objects is paramount, as well as for experimental and industrial settings requiring precise material handling. His work represents a vital step toward more perceptive and autonomous systems, bridging the gap between visual data and actionable material understanding.
Research Focus
Key Achievements
Top Papers
- 1