Cen Dai

Nanjing University of Science and Technology

Papers

Total Citations

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About

Cen Dai is a computer vision researcher whose work centers on real-time 6D object pose estimation, a critical challenge for robotics, augmented reality, and autonomous systems. Dai’s most notable contribution is the development of RTFT6D, a novel framework that leverages a Fusion Transformer architecture to achieve high-speed, accurate pose estimation from RGB-D data. This approach addresses the long-standing trade-off between computational efficiency and precision, enabling robust performance in dynamic, real-world environments. While still early in their career—with RTFT6D already garnering initial citations—Dai’s work demonstrates a clear focus on bridging deep learning and practical deployment. By integrating transformer-based attention mechanisms with efficient feature fusion, their research offers a scalable solution for tasks requiring rapid, reliable spatial understanding. Dai’s contributions are particularly relevant for applications in robotic manipulation and scene understanding, where real-time feedback is essential. As the field moves toward more lightweight, transformer-driven architectures, Dai’s work positions them as an emerging voice in advancing practical, high-performance vision systems.