activity
20192022
most citedBlind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network

938 citations · 1k across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV202218 cited

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…

cs.CV202075 cited

Language-guided Navigation via Cross-Modal Grounding and Alternate Adversarial Learning

Weixia Zhang, Chao Ma, Qi Wu +1

The emerging vision-and-language navigation (VLN) problem aims at learning to navigate an agent to the target location in unseen photo-realistic environments according to the given…

cs.CV2020

Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild

Weixia Zhang, Kede Ma, Guangtao Zhai +1

Performance of blind image quality assessment (BIQA) models has been significantly boosted by end-to-end optimization of feature engineering and quality regression. Nevertheless, d…

eess.IV2019938 cited

Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network

Weixia Zhang, Kede Ma, Jia Yan +2

We propose a deep bilinear model for blind image quality assessment (BIQA) that handles both synthetic and authentic distortions. Our model consists of two convolutional neural net…

cs.CV2019

Learning to Blindly Assess Image Quality in the Laboratory and Wild

Weixia Zhang, Kede Ma, Guangtao Zhai +1

Computational models for blind image quality assessment (BIQA) are typically trained in well-controlled laboratory environments with limited generalizability to realistically disto…