18 citations · 101 across the 15 of their papers we have counts for
10 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…