Congratulations to Zhanxuan Mei for passing his defense. Zhanxuan’s thesis is titled “Explainable and Lightweight Techniques for Blind Visual Quality Assessment and Saliency Detection.” His Dissertation Committee includes Jay Kuo (Chair), Antonio Ortega, and Ulrich Neumann (Outside Member). The Committee members praised the quality of Zhanxuan’s work very much. The MCL News team invited Zhanxuan for a short talk on his thesis and PhD experience. Here is the summary. We thank Zhanxuan for his kind sharing and wish him all the best on his next journey. A high-level abstract of Zhanxuan’s thesis is given below:
Thesis:
Explainable and Lightweight Techniques for Blind Visual Quality Assessment and Saliency Detection
The thesis contains four main research topics:
We begin by presenting our proposed GreenBIQA method, a novel approach to BIQA characterized by its compact model size, low computational complexity, and high performance. Building on the foundation of GreenBIQA, we extend its application to BVQA through the development of GreenBVQA. To further enhance the performance of GreenBIQA, we introduce a lightweight and efficient image saliency detection method, termed GreenSaliency. Ultimately, we integrate GreenSaliency with GreenBIQA, culminating in the development of the Green Saliency-guided BIQA method (GSBIQA).
PhD Experience Sharing:
The PhD journey at MCL has been an unforgettable experience. Over the course of this long and challenging path, I navigated through the unprecedented COVID era, multiple rounds of rigorous exams, and a diverse range of responsibilities, including teaching assistantships and intensive research projects. Each challenge presented an opportunity to grow, expand my perspectives, and enhance my skill set. I have honed my communication skills, developed the ability to tackle real-world problems through collaborative projects, and cultivated teamwork skills by engaging in discussions and joint efforts with exceptionally talented peers. These valuable experiences and abilities have equipped me to confidently face the challenges of my future career.
MCL truly feels like a warm and supportive family. Professor Kuo, along with my peers, have consistently been there to offer guidance, constructive feedback, and encouragement. The collaborative and nurturing environment at MCL has been instrumental in my growth, and I am deeply grateful to Professor Kuo, all MCL members, and everyone who has supported me throughout my PhD journey. Their contributions have made this experience not only professionally enriching but also personally meaningful.
