Search Results for author: Mingkai Huang

Found 4 papers, 2 papers with code

FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction

1 code implementation1 Nov 2021 Hao Zhu, Haotian Yang, Longwei Guo, Yidi Zhang, Yanru Wang, Mingkai Huang, Qiu Shen, Ruigang Yang, Xun Cao

By training on FaceScape data, a novel algorithm is proposed to predict elaborate riggable 3D face models from a single image input.

3D Face Reconstruction 3D Reconstruction

Hybrid Differentially Private Federated Learning on Vertically Partitioned Data

no code implementations6 Sep 2020 Chang Wang, Jian Liang, Mingkai Huang, Bing Bai, Kun Bai, Hao Li

We present HDP-VFL, the first hybrid differentially private (DP) framework for vertical federated learning (VFL) to demonstrate that it is possible to jointly learn a generalized linear model (GLM) from vertically partitioned data with only a negligible cost, w. r. t.

Federated Learning Privacy Preserving

A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations

no code implementations25 Aug 2020 Mingkai Huang, Hao Li, Bing Bai, Chang Wang, Kun Bai, Fei Wang

Federated Learning(FL) is a newly developed privacy-preserving machine learning paradigm to bridge data repositories without compromising data security and privacy.

Collaborative Filtering Federated Learning +1

FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction

1 code implementation CVPR 2020 Haotian Yang, Hao Zhu, Yanru Wang, Mingkai Huang, Qiu Shen, Ruigang Yang, Xun Cao

In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and propose a novel algorithm that is able to predict elaborate riggable 3D face models from a single image input.

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