activity
20172023
most citedTemporal Upsampling of Depth Maps Using a Hybrid Camera

18 citations · 101 across the 15 of their papers we have counts for

collaborators

15 papers

cs.CV2023

Unpaired Multi-domain Attribute Translation of 3D Facial Shapes with a Square and Symmetric Geometric Map

Zhenfeng Fan, Zhiheng Zhang, Shuang Yang +3

While impressive progress has recently been made in image-oriented facial attribute translation, shape-oriented 3D facial attribute translation remains an unsolved issue. This is p…

cs.GR2023★ 15 cited

Pose-aware Attention Network for Flexible Motion Retargeting by Body Part

Lei Hu, Zihao Zhang, Chongyang Zhong +2

Motion retargeting is a fundamental problem in computer graphics and computer vision. Existing approaches usually have many strict requirements, such as the source-target skeletons…

cs.GR2022★ 1 cited

Neural3Points: Learning to Generate Physically Realistic Full-body Motion for Virtual Reality Users

Yongjing Ye, Libin Liu, Lei Hu +1

Animating an avatar that reflects a user's action in the VR world enables natural interactions with the virtual environment. It has the potential to allow remote users to communica…

cs.CV2022★ 10 cited

Spatio-Temporal Gating-Adjacency GCN for Human Motion Prediction

Chongyang Zhong, Lei Hu, Zihao Zhang +2

Predicting future motion based on historical motion sequence is a fundamental problem in computer vision, and it has wide applications in autonomous driving and robotics. Some rece…

cs.CV2021

Towards Fine-grained 3D Face Dense Registration: An Optimal Dividing and Diffusing Method

Zhenfeng Fan, Silong Peng, Shihong Xia

Dense vertex-to-vertex correspondence between 3D faces is a fundamental and challenging issue for 3D&2D face analysis. While the sparse landmarks have anatomically ground-truth cor…

cs.CV2021★ 7 cited

3D-TalkEmo: Learning to Synthesize 3D Emotional Talking Head

Qianyun Wang, Zhenfeng Fan, Shihong Xia

Impressive progress has been made in audio-driven 3D facial animation recently, but synthesizing 3D talking-head with rich emotion is still unsolved. This is due to the lack of 3D…

cs.GR2020★ 6 cited

Multiscale Mesh Deformation Component Analysis with Attention-based Autoencoders

Jie Yang, Lin Gao, Qingyang Tan +3

Deformation component analysis is a fundamental problem in geometry processing and shape understanding. Existing approaches mainly extract deformation components in local regions a…

cs.CV2020★ 1 cited

A Backbone Replaceable Fine-tuning Framework for Stable Face Alignment

Xu Sun, Zhenfeng Fan, Zihao Zhang +2

Heatmap regression based face alignment has achieved prominent performance on static images. However, the stability and accuracy are remarkably discounted when applying the existin…

cs.GR2020★ 4 cited

Deep Generation of Face Images from Sketches

Shu-Yu Chen, Wanchao Su, Lin Gao +2

Recent deep image-to-image translation techniques allow fast generation of face images from freehand sketches. However, existing solutions tend to overfit to sketches, thus requiri…

cs.GR2018★ 10 cited

Combining Recurrent Neural Networks and Adversarial Training for Human Motion Synthesis and Control

Zhiyong Wang, Jinxiang Chai, Shihong Xia

This paper introduces a new generative deep learning network for human motion synthesis and control. Our key idea is to combine recurrent neural networks (RNNs) and adversarial tra…

cs.GR2017★ 1 cited

Cascaded 3D Full-body Pose Regression from Single Depth Image at 100 FPS

Shihong Xia, Zihao Zhang, Le Su

There are increasing real-time live applications in virtual reality, where it plays an important role in capturing and retargetting 3D human pose. But it is still challenging to es…

cs.GR2017★ 17 cited

Sparse Data Driven Mesh Deformation

Lin Gao, Yu-Kun Lai, Jie Yang +3

Example-based mesh deformation methods are powerful tools for realistic shape editing. However, existing techniques typically combine all the example deformation modes, which can l…

cs.GR2017★ 7 cited

Variational Autoencoders for Deforming 3D Mesh Models

Qingyang Tan, Lin Gao, Yu-Kun Lai +1

3D geometric contents are becoming increasingly popular. In this paper, we study the problem of analyzing deforming 3D meshes using deep neural networks. Deforming 3D meshes are fl…

cs.GR2017★ 4 cited

Mesh-based Autoencoders for Localized Deformation Component Analysis

Qingyang Tan, Lin Gao, Yu-Kun Lai +2

Spatially localized deformation components are very useful for shape analysis and synthesis in 3D geometry processing. Several methods have recently been developed, with an aim to…

cs.GR2017★ 18 cited

Temporal Upsampling of Depth Maps Using a Hybrid Camera

Ming-Ze Yuan, Lin Gao, Hongbo Fu +1

In recent years, consumer-level depth cameras have been adopted for various applications. However, they often produce depth maps at only a moderately high frame rate (approximately…