9 citations · 16 across the 18 of their papers we have counts for
5 papers · 1 filter
Source-free Unsupervised Domain Adaptation for Blind Image Quality Assessment
Jianzhao Liu, Xin Li, Shukun An +1
Existing learning-based methods for blind image quality assessment (BIQA) are heavily dependent on large amounts of annotated training data, and usually suffer from a severe perfor…
StyleAM: Perception-Oriented Unsupervised Domain Adaption for Non-reference Image Quality Assessment
Yiting Lu, Xin Li, Jianzhao Liu +1
Deep neural networks (DNNs) have shown great potential in non-reference image quality assessment (NR-IQA). However, the annotation of NR-IQA is labor-intensive and time-consuming,…
Stroke-Based Autoencoders: Self-Supervised Learners for Efficient Zero-Shot Chinese Character Recognition
Zongze Chen, Wenxia Yang, Xin Li
Chinese characters carry a wealth of morphological and semantic information; therefore, the semantic enhancement of the morphology of Chinese characters has drawn significant atten…
RTN: Reinforced Transformer Network for Coronary CT Angiography Vessel-level Image Quality Assessment
Yiting Lu, Jun Fu, Xin Li +6
Coronary CT Angiography (CCTA) is susceptible to various distortions (e.g., artifacts and noise), which severely compromise the exact diagnosis of cardiovascular diseases. The appr…
SwinIQA: Learned Swin Distance for Compressed Image Quality Assessment
Jianzhao Liu, Xin Li, Yanding Peng +2
Image compression has raised widespread interest recently due to its significant importance for multimedia storage and transmission. Meanwhile, a reliable image quality assessment…