40 citations · 61 across the 11 of their papers we have counts for
11 papers
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…
The Taming of the Screw: Dislocation Cores in BCC Metals and Alloys
Rui Wang, Lingyu Zhu, Subrahmanyam Pattamatta +2
Body-centred cubic (BCC) transition metals tend to be brittle at low temperatures, posing significant challenges in processing and major concerns for damage tolerance. The brittlen…
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…
Beyond Visual Field of View: Perceiving 3D Environment with Echoes and Vision
Lingyu Zhu, Esa Rahtu, Hang Zhao
This paper focuses on perceiving and navigating 3D environments using echoes and RGB image. In particular, we perform depth estimation by fusing RGB image with echoes, received fro…
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…
V-SlowFast Network for Efficient Visual Sound Separation
Lingyu Zhu, Esa Rahtu
The objective of this paper is to perform visual sound separation: i) we study visual sound separation on spectrograms of different temporal resolutions; ii) we propose a new light…
No-Reference Image Quality Assessment by Hallucinating Pristine Features
Baoliang Chen, Lingyu Zhu, Chenqi Kong +3
In this paper, we propose a no-reference (NR) image quality assessment (IQA) method via feature level pseudo-reference (PR) hallucination. The proposed quality assessment framework…
Visually Guided Sound Source Separation and Localization using Self-Supervised Motion Representations
Lingyu Zhu, Esa Rahtu
The objective of this paper is to perform audio-visual sound source separation, i.e.~to separate component audios from a mixture based on the videos of sound sources. Moreover, we…
Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality Assessment
Baoliang Chen, Lingyu Zhu, Guo Li +2
In this work, we propose a no-reference video quality assessment method, aiming to achieve high-generalization capability in cross-content, -resolution and -frame rate quality pred…
Visually Guided Sound Source Separation using Cascaded Opponent Filter Network
Lingyu Zhu, Esa Rahtu
The objective of this paper is to recover the original component signals from a mixture audio with the aid of visual cues of the sound sources. Such task is usually referred as vis…
Leveraging Category Information for Single-Frame Visual Sound Source Separation
Lingyu Zhu, Esa Rahtu
Visual sound source separation aims at identifying sound components from a given sound mixture with the presence of visual cues. Prior works have demonstrated impressive results, b…