no code implementations • 16 Nov 2021 • Mingxin Yang, Jianwei Guo, Zhanglin Cheng, Xiaopeng Zhang, Dong-Ming Yan
Although each method has its own advantage, none of them is capable of recovering a high-fidelity and re-renderable facial texture, where the term 're-renderable' demands the facial texture to be spatially complete and disentangled with environmental illumination.
no code implementations • 26 Oct 2021 • Jin Zhang, Mingyang Zhao, Xin Jiang, Dong-Ming Yan
The proposed method assumes each data point is generated by a Laplacian Mixture Model (LMM), where its centers are determined by the corresponding points in other point sets.
no code implementations • 28 Sep 2021 • Qiang Fu, Dong-Ming Yan, Wolfgang Heidrich
We demonstrate and verify the imaging performance with a prototype Voronoi-Fresnel lensless camera on a 1. 6-megapixel image sensor in various illumination conditions.
1 code implementation • 16 Aug 2021 • Shiyu Hou, Chaoqun Wang, Weize Quan, Jingen Jiang, Dong-Ming Yan
The core goal is to improve the accuracy of text detection and recognition by removing the highlight from text images.
1 code implementation • 15 Mar 2021 • Xiaolong Yang, Xiaohong Jia, Dihong Gong, Dong-Ming Yan, Zhifeng Li, Wei Liu
We prove that face rotation in the image space is equivalent to an additive residual component in the feature space of CNNs, which is determined solely by the rotation.
1 code implementation • 19 Nov 2020 • Xuewei Bian, Chaoqun Wang, Weize Quan, Juntao Ye, Xiaopeng Zhang, Dong-Ming Yan
Specifically, we decouple the text removal problem into text stroke detection and stroke removal.
no code implementations • 4 Nov 2020 • Ruisong Zhang, Weize Quan, Baoyuan Wu, Zhifeng Li, Dong-Ming Yan
Recent GAN-based image inpainting approaches adopt an average strategy to discriminate the generated image and output a scalar, which inevitably lose the position information of visual artifacts.
no code implementations • 28 Jan 2020 • Yiqun Wang, Jing Ren, Dong-Ming Yan, Jianwei Guo, Xiaopeng Zhang, Peter Wonka
Second, we propose a new multiscale graph convolutional network (MGCN) to transform a non-learned feature to a more discriminative descriptor.
no code implementations • 17 Feb 2019 • Weize Quan, Dong-Ming Yan, Kai Wang, Xiaopeng Zhang, Denis Pellerin
First, we design and implement a base network, which can attain better performance in terms of classification accuracy and generalization (in most cases) compared with state-of-the-art methods.
no code implementations • ECCV 2018 • Hanyu Wang, Jianwei Guo, Dong-Ming Yan, Weize Quan, Xiaopeng Zhang
In this paper, we present a novel deep learning framework that derives discriminative local descriptors for 3D surface shapes.