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Title: Innovations of Zheng Wang in Pedestrian Re-identification
Introduction
Zheng Wang is an accomplished inventor based in Hubei, China. He has made significant contributions to the field of pedestrian re-identification through his innovative methods. His work focuses on enhancing the accuracy and efficiency of identifying individuals in various environments.
Latest Patents
Zheng Wang holds a patent for a "Pedestrian re-identification method based on virtual samples." This invention proposes a novel approach that involves several key steps. First, it obtains virtual persons generated by a game engine and creates virtual samples with person labels by fusing a background of a target dataset with the pose of real individuals through a multi-factor variational generation network. Next, it renders the generated virtual samples according to specific lighting conditions. The method then samples the rendered virtual samples based on the person attributes of the target dataset. Finally, it constructs a training dataset from the sampled virtual samples to train a pedestrian re-identification model and verifies the identification effectiveness of the trained model. This innovative framework integrates translation, rendering, and sampling to minimize the distribution gap between virtual and real images, making it highly applicable to pedestrian datasets in real-world scenarios.
Career Highlights
Zheng Wang is affiliated with Wuhan University, where he continues to advance his research and development in the field of pedestrian re-identification. His work has garnered attention for its practical applications and innovative methodologies.
Collaborations
Zheng Wang collaborates with Xiaoyang Guo, contributing to the advancement of their shared research interests and enhancing the impact of their work in the field.
Conclusion
Zheng Wang's contributions to pedestrian re-identification through his innovative patent demonstrate his commitment to advancing technology in this area. His work not only enhances identification methods but also paves the way for future innovations in real-world applications.