17 citations · 29 across the 9 of their papers we have counts for
9 papers
HDRFace: Rethinking Face Restoration with High-Dimensional Representation
Zirui Wang, Xianhui Lin, Yi Dong +7
Face restoration under complex degradations still remains an ill-posed inverse problem due to severe information loss. Although diffusion models benefit from strong generative prio…
HD-Fusion: Detailed Text-to-3D Generation Leveraging Multiple Noise Estimation
Jinbo Wu, Xiaobo Gao, Xing Liu +5
In this paper, we study Text-to-3D content generation leveraging 2D diffusion priors to enhance the quality and detail of the generated 3D models. Recent progress (Magic3D) in text…
Pushing the Envelope of Thin Crack Detection
Liang Xu, Taro Hatsutani, Xing Liu +3
In this study, we consider the problem of detecting cracks from the image of a concrete surface for automated inspection of infrastructure, such as bridges. Its overall accuracy is…
Unsupervised Image Super-Resolution with an Indirect Supervised Path
Zhen Han, Enyan Dai, Xu Jia +5
The task of single image super-resolution (SISR) aims at reconstructing a high-resolution (HR) image from a low-resolution (LR) image. Although significant progress has been made b…
Restoring Images with Unknown Degradation Factors by Recurrent Use of a Multi-branch Network
Xing Liu, Masanori Suganuma, Xiyang Luo +1
The employment of convolutional neural networks has achieved unprecedented performance in the task of image restoration for a variety of degradation factors. However, high-performa…
Evaluating Artificial Systems for Pairwise Ranking Tasks Sensitive to Individual Differences
Xing Liu, Takayuki Okatani
Owing to the advancement of deep learning, artificial systems are now rival to humans in several pattern recognition tasks, such as visual recognition of object categories. However…
Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
Xing Liu, Masanori Suganuma, Zhun Sun +1
In this paper, we study design of deep neural networks for tasks of image restoration. We propose a novel style of residual connections dubbed "dual residual connection", which exp…
Attention-based Adaptive Selection of Operations for Image Restoration in the Presence of Unknown Combined Distortions
Masanori Suganuma, Xing Liu, Takayuki Okatani
Many studies have been conducted so far on image restoration, the problem of restoring a clean image from its distorted version. There are many different types of distortion which…
Integrating Deep Features for Material Recognition
Yan Zhang, Mete Ozay, Xing Liu +1
We propose a method for integration of features extracted using deep representations of Convolutional Neural Networks (CNNs) each of which is learned using a different image datase…