32 citations · 87 across the 19 of their papers we have counts for
7 papers · 1 filter
DeepDC: Deep Distance Correlation as a Perceptual Image Quality Evaluator
Hanwei Zhu, Baoliang Chen, Lingyu Zhu +2
ImageNet pre-trained deep neural networks (DNNs) show notable transferability for building effective image quality assessment (IQA) models. Such a remarkable byproduct has often be…
Learning from Mixed Datasets: A Monotonic Image Quality Assessment Model
Zhaopeng Feng, Keyang Zhang, Shuyue Jia +2
Deep learning based image quality assessment (IQA) models usually learn to predict image quality from a single dataset, leading the model to overfit specific scenes. To account for…
Just Noticeable Difference Modeling for Face Recognition System
Yu Tian, Zhangkai Ni, Baoliang Chen +4
High-quality face images are required to guarantee the stability and reliability of automatic face recognition (FR) systems in surveillance and security scenarios. However, a massi…
Deep Feature Statistics Mapping for Generalized Screen Content Image Quality Assessment
Baoliang Chen, Hanwei Zhu, Lingyu Zhu +2
The statistical regularities of natural images, referred to as natural scene statistics, play an important role in no-reference image quality assessment. However, it has been widel…
DeepWSD: Projecting Degradations in Perceptual Space to Wasserstein Distance in Deep Feature Space
Xingran Liao, Baoliang Chen, Hanwei Zhu +3
Existing deep learning-based full-reference IQA (FR-IQA) models usually predict the image quality in a deterministic way by explicitly comparing the features, gauging how severely…
The Loop Game: Quality Assessment and Optimization for Low-Light Image Enhancement
Danni Huang, Lingyu Zhu, Zihao Lin +3
There is an increasing consensus that the design and optimization of low light image enhancement methods need to be fully driven by perceptual quality. With numerous approaches pro…