Shuqiang Jiang

Chinese Academy of Sciences, Institute of Computing Technology

Papers

Total Citations

130

H-Index

About

Shuqiang Jiang is a leading researcher in computer vision, with a focus on instance-level object retrieval and recognition, a domain that moves beyond generic category classification to identify specific objects. His seminal work, "INSTRE" (2015, 81 citations), addressed this critical gap, establishing a benchmark that has driven significant advances in fine-grained visual search. More recently, Jiang has pioneered the integration of attention mechanisms into deep learning for agricultural applications, as demonstrated in his 2023 paper on vision-based fruit recognition using a multi-scale attention CNN (40 citations). This work showcases his commitment to translating foundational vision research into practical, real-world solutions. Jiang also explores the frontier of embodied AI, investigating how autonomous agents can generate natural language explanations for their actions based on visual observation, a key step toward building trust in human-robot collaboration. His contributions span from foundational benchmarks to cutting-edge applications in robotics and agriculture, consistently pushing the boundaries of how machines perceive and interact with the visual world.