Stanford, CA, United States of America

De-An Huang


Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: De-An Huang: Innovator in Video Captioning Technology

Introduction

De-An Huang is a notable inventor based in Stanford, CA, who has made significant contributions to the field of video captioning technology. With a focus on enhancing scene perception through innovative methods, Huang's work is paving the way for advancements in how we understand and interpret video content.

Latest Patents

Huang holds a patent titled "Spatio-temporal graph for video captioning with knowledge distillation." This patent describes a method for scene perception using video captioning based on a spatio-temporal graph model. The method involves decomposing the spatio-temporal graph model of a scene in input video into a spatial graph and a temporal graph. It also includes modeling a two-branch framework with an object branch and a scene branch according to the spatial and temporal graphs to learn object interactions. Furthermore, the method transfers the learned object interactions from the object branch to the scene branch as privileged information, ultimately captioning the scene by aligning language logits from both branches based on the learned interactions. Huang's innovative approach is encapsulated in 1 patent.

Career Highlights

Throughout his career, De-An Huang has worked with esteemed organizations such as the Toyota Research Institute and Leland Stanford Junior University. His experience in these institutions has allowed him to refine his skills and contribute to groundbreaking research in video technology.

Collaborations

Huang has collaborated with talented individuals, including Boxiao Pan and Haoye Cai, who have contributed to his research endeavors.

Conclusion

De-An Huang's work in video captioning technology exemplifies the innovative spirit of modern inventors. His contributions are not only advancing the field but also enhancing our understanding of video content interpretation.

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