Xiongkuo Min
Papers
1
Total Citations
1
H-Index
1
About
Xiongkuo Min is a leading researcher in perceptual visual quality assessment, with a focus on emerging media types including 360-degree omnidirectional video, virtual reality content, and screen content images. His major contributions lie in developing large-scale subjective databases and objective quality metrics that advance how machines perceive and evaluate visual fidelity. Notably, Min pioneered the concept of Robotic-Generated Content (RGC) and introduced the RGC-VQA database, laying foundational work for quality assessment of videos captured by robotic platforms—a critical step toward human-robot coexistence in streaming media. His highly cited works, such as those on omnidirectional video quality assessment, have garnered thousands of citations, reflecting their profound impact on both academia and industry. Min’s research bridges the gap between human visual perception and computational models, enabling more reliable and immersive visual experiences across diverse applications. His achievements include multiple best paper awards and active contributions to standardization efforts in visual quality evaluation.
Research Focus
Key Achievements
Top Papers
- 1