activity
20202026
most citedTowards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networks

10 citations · 18 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Anchor3DGS: Feed-Forward 3D Gaussian Splatting with Compact Anchor-Based Representation

Sheng Ye, Jiangke Lin, Fudong Wang +3

Recent feed-forward 3D Gaussian Splatting (3DGS) methods have enabled effective multi-view 3D reconstruction by predicting Gaussian primitives in a single forward pass. However, ex…

cs.CV2023★ 8 cited

High-Quality 3D Face Reconstruction with Affine Convolutional Networks

Zhiqian Lin, Jiangke Lin, Lincheng Li +2

Recent works based on convolutional encoder-decoder architecture and 3DMM parameterization have shown great potential for canonical view reconstruction from a single input image. C…

cs.CV2023

Exploring the Relationship between Samples and Masks for Robust Defect Localization

Jiang Lin, Yaping Yan

Defect detection aims to detect and localize regions out of the normal distribution.Previous approaches model normality and compare it with the input to identify defective regions,…

cs.CV2021

MeInGame: Create a Game Character Face from a Single Portrait

Jiangke Lin, Yi Yuan, Zhengxia Zou

Many deep learning based 3D face reconstruction methods have been proposed recently, however, few of them have applications in games. Current game character customization systems e…

cs.CV2020★ 10 cited

Towards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networks

Jiangke Lin, Yi Yuan, Tianjia Shao +1

3D Morphable Model (3DMM) based methods have achieved great success in recovering 3D face shapes from single-view images. However, the facial textures recovered by such methods lac…