Search Results for author: Yufeng Liu

Found 15 papers, 4 papers with code

MobRecon: Mobile-Friendly Hand Mesh Reconstruction from Monocular Image

1 code implementation6 Dec 2021 Xingyu Chen, Yufeng Liu, Yajiao Dong, Xiong Zhang, Chongyang Ma, Yanmin Xiong, Yuan Zhang, Xiaoyan Guo

Overall, our hand reconstruction framework, called MobRecon, comprises affordable computational costs and miniature model size, which reaches a high inference speed of 83FPS on Apple A14 CPU.

Rejoinder: Learning Optimal Distributionally Robust Individualized Treatment Rules

no code implementations17 Oct 2021 Weibin Mo, Zhengling Qi, Yufeng Liu

However, when the growth of testing sample size available for training is in a slower order, efficient value function estimates may not perform well anymore.

Efficient Learning of Optimal Individualized Treatment Rules for Heteroscedastic or Misspecified Treatment-Free Effect Models

1 code implementation6 Sep 2021 Weibin Mo, Yufeng Liu

Other than potential misspecified nuisance models, most existing methods do not account for the potential problem when the variance of outcome is heterogeneous among covariates and treatment.

Decision Making

Improving Robustness for Pose Estimation via Stable Heatmap Regression

no code implementations8 May 2021 Yumeng Zhang, Li Chen, Yufeng Liu, Xiaoyan Guo, Wen Zheng, Junhai Yong

Deep learning methods have achieved excellent performance in pose estimation, but the lack of robustness causes the keypoints to change drastically between similar images.

Pose Estimation

Regressive Domain Adaptation for Unsupervised Keypoint Detection

1 code implementation CVPR 2021 Junguang Jiang, Yifei Ji, Ximei Wang, Yufeng Liu, Jianmin Wang, Mingsheng Long

First, based on our observation that the probability density of the output space is sparse, we introduce a spatial probability distribution to describe this sparsity and then use it to guide the learning of the adversarial regressor.

Domain Adaptation Keypoint Detection

Camera-Space Hand Mesh Recovery via Semantic Aggregation and Adaptive 2D-1D Registration

1 code implementation CVPR 2021 Xingyu Chen, Yufeng Liu, Chongyang Ma, Jianlong Chang, Huayan Wang, Tian Chen, Xiaoyan Guo, Pengfei Wan, Wen Zheng

In the root-relative mesh recovery task, we exploit semantic relations among joints to generate a 3D mesh from the extracted 2D cues.

Learning Optimal Distributionally Robust Individualized Treatment Rules

no code implementations26 Jun 2020 Weibin Mo, Zhengling Qi, Yufeng Liu

We propose a novel distributionally robust ITR (DR-ITR) framework that maximizes the worst-case value function across the values under a set of underlying distributions that are "close" to the training distribution.

Decision Making

Statistical Analysis of Stationary Solutions of Coupled Nonconvex Nonsmooth Empirical Risk Minimization

no code implementations6 Oct 2019 Zhengling Qi, Ying Cui, Yufeng Liu, Jong-Shi Pang

This paper has two main goals: (a) establish several statistical properties---consistency, asymptotic distributions, and convergence rates---of stationary solutions and values of a class of coupled nonconvex and nonsmoothempirical risk minimization problems, and (b) validate these properties by a noisy amplitude-based phase retrieval problem, the latter being of much topical interest. Derived from available data via sampling, these empirical risk minimization problems are the computational workhorse of a population risk model which involves the minimization of an expected value of a random functional.

Adaptive Wasserstein Hourglass for Weakly Supervised Hand Pose Estimation from Monocular RGB

no code implementations11 Sep 2019 Yumeng Zhang, Li Chen, Yufeng Liu, Junhai Yong, Wen Zheng

During training, based on the relation between these common characteristics and 3D pose learned from fully-annotated synthetic datasets, it is beneficial for the network to restore the 3D pose of weakly labeled real-world datasets with the aid of 2D annotations and depth images.

3D Hand Pose Estimation Domain Adaptation

Estimation of Individualized Decision Rules Based on an Optimized Covariate-Dependent Equivalent of Random Outcomes

no code implementations27 Aug 2019 Zhengling Qi, Ying Cui, Yufeng Liu, Jong-Shi Pang

Recent exploration of optimal individualized decision rules (IDRs) for patients in precision medicine has attracted a lot of attention due to the heterogeneous responses of patients to different treatments.

Decision Making

Stability Enhanced Large-Margin Classifier Selection

no code implementations20 Jan 2017 Will Wei Sun, Guang Cheng, Yufeng Liu

Stability is an important aspect of a classification procedure because unstable predictions can potentially reduce users' trust in a classification system and also harm the reproducibility of scientific conclusions.

General Classification

Simultaneous Clustering and Estimation of Heterogeneous Graphical Models

no code implementations28 Nov 2016 Botao Hao, Will Wei Sun, Yufeng Liu, Guang Cheng

We consider joint estimation of multiple graphical models arising from heterogeneous and high-dimensional observations.

Sparse Learning

Joint Estimation of Multiple Dependent Gaussian Graphical Models with Applications to Mouse Genomics

no code implementations30 Aug 2016 Yuying Xie, Yufeng Liu, William Valdar

In this paper, we propose a novel estimator for data arising from a group of Gaussian graphical models that are themselves dependent.

Large-Margin Classification with Multiple Decision Rules

no code implementations19 Nov 2014 Patrick K. Kimes, D. Neil Hayes, J. S. Marron, Yufeng Liu

Binary classification is a common statistical learning problem in which a model is estimated on a set of covariates for some outcome indicating the membership of one of two classes.

General Classification

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