no code implementations • 26 Feb 2024 • Xiang Chen, Faqiang Wang, Jun Liu, Li Cui
The algorithm (1) converges to the true solution of UOT, (2) has theoretical guarantees and robust regularization parameter selection, (3) mitigates numerical stability issues, and (4) can achieve comparable computational complexity to the Scaling algorithm in specific practice.
no code implementations • 18 May 2023 • Lihui Qian, Xintong Han, Faqiang Wang, Hongyu Liu, Haoye Dong, Zhiwen Li, Huawei Wei, Zhe Lin, Cheng-Bin Jin
We present XFormer, a novel human mesh and motion capture method that achieves real-time performance on consumer CPUs given only monocular images as input.
Ranked #32 on 3D Human Pose Estimation on 3DPW
1 code implementation • 22 Feb 2023 • Hongyu Liu, Xintong Han, ChengBin Jin, Lihui Qian, Huawei Wei, Zhe Lin, Faqiang Wang, Haoye Dong, Yibing Song, Jia Xu, Qifeng Chen
In this paper, we propose Human MotionFormer, a hierarchical ViT framework that leverages global and local perceptions to capture large and subtle motion matching, respectively.
no code implementations • 6 Jun 2018 • Faqiang Wang, Cuicui Zhao, Jun Liu, Hai-yang Huang
Thus, the segmentation results of the existing Ncut method are largely dependent on a pre-constructed similarity measure on the graph since this measure is usually given empirically by users.
no code implementations • 21 May 2018 • Faqiang Wang, Hai-yang Huang, Jun Liu
In this paper, the traditional model based variational method and learning based algorithms are naturally integrated to address mixed noise removal problem.
no code implementations • 26 Mar 2018 • Ibrahim Omara, Hongzhi Zhang, Faqiang Wang, WangMeng Zuo
Ear recognition task is known as predicting whether two ear images belong to the same person or not.
no code implementations • CVPR 2016 • Faqiang Wang, WangMeng Zuo, Liang Lin, David Zhang, Lei Zhang
Person re-identification has been usually solved as either the matching of single-image representation (SIR) or the classification of cross-image representation (CIR).
no code implementations • 2 Feb 2015 • Wangmeng Zuo, Faqiang Wang, David Zhang, Liang Lin, Yuchi Huang, Deyu Meng, Lei Zhang
Distance metric learning aims to learn from the given training data a valid distance metric, with which the similarity between data samples can be more effectively evaluated for classification.
no code implementations • 23 Sep 2013 • Faqiang Wang, WangMeng Zuo, Lei Zhang, Deyu Meng, David Zhang
Learning a distance metric from the given training samples plays a crucial role in many machine learning tasks, and various models and optimization algorithms have been proposed in the past decade.