Yanqing Jing

Papers

Total Citations

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About

Yanqing Jing is a researcher at the forefront of computer vision and artificial intelligence, with a primary focus on 3D human pose estimation and game AI. Jing’s most significant contribution is the development of **FreeMan**, a groundbreaking benchmark introduced in 2024 that addresses the critical challenge of estimating 3D human body structure from complex, real-world natural scenes. This work, which has already garnered 9 citations, is vital for advancing fields like AI-generated content (AIGC) and human-robot interaction, providing a foundational tool for understanding and interacting with human actions in uncontrolled environments. Prior to this, Jing demonstrated versatility by exploring AI strategies for turn-based games, proposing a hybrid approach that combines Gradient Boosting Decision Trees (GBDT), Logistic Regression (LR), and deep learning to generate intelligent fighting tactics for the game *StoneAge 2*. This earlier work, with 4 citations, showcases a deep understanding of both classical machine learning and modern neural networks. Through these contributions, Yanqing Jing is establishing a reputation for building practical, real-world AI systems that bridge the gap between controlled lab settings and the messy, dynamic conditions of everyday life.