Zhipeng Ye

Papers

Total Citations

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About

Zhipeng Ye is a researcher specializing in computer vision and robotics, with a particular focus on indoor scene understanding and hierarchical inference methods. His work addresses the challenge of enabling service robots to interpret and interact with complex indoor environments, where variations in layout and decoration make classification difficult. In his notable 2017 paper, "A hierarchical inferential method for indoor scene classification," Ye introduced a knowledge-based approach that leverages visual attributes to improve scene recognition accuracy—a contribution that has garnered 2 citations and laid groundwork for more robust robotic perception systems. By integrating hierarchical reasoning with visual cues, his research bridges the gap between low-level image features and high-level semantic understanding, advancing the field of autonomous navigation and human-robot interaction. Ye’s work is particularly relevant for students and researchers interested in embodied AI, scene parsing, and the practical deployment of intelligent systems in real-world settings.