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Timin Gao

2 accepted papers

2024

Adaptive Feature Selection for No-Reference Image Quality Assessment by Mitigating Semantic Noise Sensitivity

ICML 2024poster

The current state-of-the-art No-Reference Image Quality Assessment (NR-IQA) methods typically rely on feature extraction from upstream semantic backbone networks, assuming that all extracted features are relevant. However, we make a key observation that not all features are beneficial, and some may…

Cited by 4SourcePDFScholar
2024

Semi-Supervised Blind Image Quality Assessment through Knowledge Distillation and Incremental Learning

AAAI 2024technical

Blind Image Quality Assessment (BIQA) aims to simulate human assessment of image quality. It has a great demand for labeled data, which is often insufficient in practice. Some researchers employ unsupervised methods to address this issue, which is challenging to emulate the human subjective system.…

Cited by 8SourcePDFScholar