Search Results for author: Shaohua Pan

Found 8 papers, 1 papers with code

Fusing Monocular Images and Sparse IMU Signals for Real-time Human Motion Capture

1 code implementation1 Sep 2023 Shaohua Pan, Qi Ma, Xinyu Yi, Weifeng Hu, Xiong Wang, Xingkang Zhou, Jijunnan Li, Feng Xu

We believe that the combination is complementary and able to solve the inherent difficulties of using one modality input, including occlusions, extreme lighting/texture, and out-of-view for visual mocap and global drifts for inertial mocap.

3D Human Pose Estimation

EgoLocate: Real-time Motion Capture, Localization, and Mapping with Sparse Body-mounted Sensors

no code implementations2 May 2023 Xinyu Yi, Yuxiao Zhou, Marc Habermann, Vladislav Golyanik, Shaohua Pan, Christian Theobalt, Feng Xu

We integrate the two techniques together in EgoLocate, a system that simultaneously performs human motion capture (mocap), localization, and mapping in real time from sparse body-mounted sensors, including 6 inertial measurement units (IMUs) and a monocular phone camera.

Simultaneous Localization and Mapping

An inexact LPA for DC composite optimization and application to matrix completions with outliers

no code implementations29 Mar 2023 Ting Tao, Ruyu Liu, Shaohua Pan

For this class of nonconvex and nonsmooth problems, we propose an inexact linearized proximal algorithm (iLPA) by computing in each step an inexact minimizer of a strongly convex majorization constructed with a partial linearization of their objective functions at the current iterate, and establish the convergence of the generated iterate sequence under the Kurdyka-\L\"ojasiewicz (KL) property of a potential function.

Column $\ell_{2,0}$-norm regularized factorization model of low-rank matrix recovery and its computation

no code implementations24 Aug 2020 Ting Tao, Yitian Qian, Shaohua Pan

This paper is concerned with the column $\ell_{2, 0}$-regularized factorization model of low-rank matrix recovery problems and its computation.

Matrix Completion

Error bound of critical points and KL property of exponent $1/2$ for squared F-norm regularized factorization

no code implementations11 Nov 2019 Ting Tao, Shaohua Pan, Shujun Bi

This paper is concerned with the squared F(robenius)-norm regularized factorization form for noisy low-rank matrix recovery problems.

KL property of exponent $1/2$ of $\ell_{2,0}$-norm and DC regularized factorizations for low-rank matrix recovery

no code implementations24 Aug 2019 Shujun Bi, Ting Tao, Shaohua Pan

To cater for the scenario in which only a coarse estimation is available for the rank of the true matrix, an $\ell_{2, 0}$-norm regularized term is added to the factored loss function to reduce the rank adaptively; and account for the ambiguities in the factorization, a balanced term is then introduced.

Equivalent Lipschitz surrogates for zero-norm and rank optimization problems

no code implementations30 Apr 2018 Yulan Liu, Shujun Bi, Shaohua Pan

Specifically, we reformulate these combinatorial problems as equivalent MPECs by the variational characterization of the zero-norm and rank function, show that their penalized problems, yielded by moving the equilibrium constraint into the objective, are the global exact penalization, and obtain the equivalent Lipschitz surrogates by eliminating the dual variable in the global exact penalty.

A Rank-Corrected Procedure for Matrix Completion with Fixed Basis Coefficients

no code implementations13 Oct 2012 Weimin Miao, Shaohua Pan, Defeng Sun

To seek a solution of high recovery quality beyond the reach of the nuclear norm, in this paper, we propose a rank-corrected procedure using a nuclear semi-norm to generate a new estimator.

Low-Rank Matrix Completion Quantum State Tomography

Cannot find the paper you are looking for? You can Submit a new open access paper.