141 citations · 251 across the 7 of their papers we have counts for
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SEGA: A Transferable Signed Ensemble Gaussian Black-Box Attack against No-Reference Image Quality Assessment Models
Yujia Liu, Dingquan Li, Zhixuan Li +1
No-Reference Image Quality Assessment (NR-IQA) models play an important role in various real-world applications. Recently, adversarial attacks against NR-IQA models have attracted…
Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization
Yujia Liu, Chenxi Yang, Dingquan Li +2
The task of No-Reference Image Quality Assessment (NR-IQA) is to estimate the quality score of an input image without additional information. NR-IQA models play a crucial role in t…
Exploring Vulnerabilities of No-Reference Image Quality Assessment Models: A Query-Based Black-Box Method
Chenxi Yang, Yujia Liu, Dingquan Li +1
No-Reference Image Quality Assessment (NR-IQA) aims to predict image quality scores consistent with human perception without relying on pristine reference images, serving as a cruc…
Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop
Weixia Zhang, Dingquan Li, Xiongkuo Min +4
No-reference image quality assessment (NR-IQA) aims to quantify how humans perceive visual distortions of digital images without access to their undistorted references. NR-IQA mode…
Deep Geometry Post-Processing for Decompressed Point Clouds
Xiaoqing Fan, Ge Li, Dingquan Li +3
Point cloud compression plays a crucial role in reducing the huge cost of data storage and transmission. However, distortions can be introduced into the decompressed point clouds d…
Semi-Supervised Deep Ensembles for Blind Image Quality Assessment
Zhihua Wang, Dingquan Li, Kede Ma
Ensemble methods are generally regarded to be better than a single model if the base learners are deemed to be "accurate" and "diverse." Here we investigate a semi-supervised ensem…