no code implementations • 7 Jun 2024 • Ting Tao, Yitian Qian, Shaohua Pan
This paper concerns a class of low-rank composite factorization models arising from matrix completion.
1 code implementation • 1 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.
Ranked #1 on 3D Human Pose Estimation on AIST++
no code implementations • 2 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.
no code implementations • 29 Mar 2023 • Ting Tao, Ruyu Liu, Shaohua Pan
This paper concerns a class of DC composite optimization problems which, as an extension of convex composite optimization problems and DC programs with nonsmooth components, often arises in robust factorization models of low-rank matrix recovery.
no code implementations • 24 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.
no code implementations • 11 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.
no code implementations • 24 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.
no code implementations • 30 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.
no code implementations • 13 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.