22 citations · 57 across the 4 of their papers we have counts for
4 papers
FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction
Hao Zhu, Haotian Yang, Longwei Guo +7
In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and the corresponding benchmark to evaluate single-view facial 3D reconstruction. By training on FaceSc…
Hybrid Differentially Private Federated Learning on Vertically Partitioned Data
Chang Wang, Jian Liang, Mingkai Huang +3
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 l…
A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations
Mingkai Huang, Hao Li, Bing Bai +3
Privacy-preserving recommendations are recently gaining momentum, since the decentralized user data is increasingly harder to collect, by recommendation service providers, due to t…
FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction
Haotian Yang, Hao Zhu, Yanru Wang +4
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 i…