352 citations · 655 across the 13 of their papers we have counts for
14 papers
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…
Beyond Score Changes: Adversarial Attack on No-Reference Image Quality Assessment from Two Perspectives
Chenxi Yang, Yujia Liu, Dingquan Li +2
Deep neural networks have demonstrated impressive success in No-Reference Image Quality Assessment (NR-IQA). However, recent researches highlight the vulnerability of NR-IQA models…
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…
Image Quality Assessment: Integrating Model-Centric and Data-Centric Approaches
Peibei Cao, Dingquan Li, Kede Ma
Learning-based image quality assessment (IQA) has made remarkable progress in the past decade, but nearly all consider the two key components -- model and data -- in isolation. Spe…
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…
Continual Learning for Blind Image Quality Assessment
Weixia Zhang, Dingquan Li, Chao Ma +3
The explosive growth of image data facilitates the fast development of image processing and computer vision methods for emerging visual applications, meanwhile introducing novel di…
Unified Quality Assessment of In-the-Wild Videos with Mixed Datasets Training
Dingquan Li, Tingting Jiang, Ming Jiang
Video quality assessment (VQA) is an important problem in computer vision. The videos in computer vision applications are usually captured in the wild. We focus on automatically as…
Norm-in-Norm Loss with Faster Convergence and Better Performance for Image Quality Assessment
Dingquan Li, Tingting Jiang, Ming Jiang
Currently, most image quality assessment (IQA) models are supervised by the MAE or MSE loss with empirically slow convergence. It is well-known that normalization can facilitate fa…
Quality Assessment of In-the-Wild Videos
Dingquan Li, Tingting Jiang, Ming Jiang
Quality assessment of in-the-wild videos is a challenging problem because of the absence of reference videos and shooting distortions. Knowledge of the human visual system can help…
Quality Assessment for Tone-Mapped HDR Images Using Multi-Scale and Multi-Layer Information
Qin He, Dingquan Li, Tingting Jiang +1
Tone mapping operators and multi-exposure fusion methods allow us to enjoy the informative contents of high dynamic range (HDR) images with standard dynamic range devices, but also…
Exploiting High-Level Semantics for No-Reference Image Quality Assessment of Realistic Blur Images
Dingquan Li, Tingting Jiang, Ming Jiang
To guarantee a satisfying Quality of Experience (QoE) for consumers, it is required to measure image quality efficiently and reliably. The neglect of the high-level semantic inform…