Jingru Li

Papers

Total Citations

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About

Jingru Li is a researcher in computer vision, with a primary focus on video object tracking and deep learning. Her most-cited work, the 2019 review "Review on Video Object Tracking Based on Deep Learning," has garnered 35 citations and provides a comprehensive survey of deep learning-based tracking algorithms, addressing persistent challenges such as occlusion, illumination variation, and real-time performance in applications ranging from video surveillance to robotics and human-computer interaction. This review synthesizes the evolution of tracking methods, highlighting the transition from traditional handcrafted features to end-to-end deep neural networks, and identifies key open problems that continue to shape the field. Li’s contribution lies in offering a structured taxonomy and critical analysis that helps researchers and practitioners navigate the rapidly growing body of work in deep tracking. By systematically evaluating state-of-the-art approaches and their limitations, her work serves as a foundational reference for those entering or advancing in video object tracking, underscoring her role in consolidating knowledge and guiding future innovation in this dynamic area of computer vision.