7 citations · 18 across the 7 of their papers we have counts for
7 papers
A Repulsive Force Unit for Garment Collision Handling in Neural Networks
Qingyang Tan, Yi Zhou, Tuanfeng Wang +3
Despite recent success, deep learning-based methods for predicting 3D garment deformation under body motion suffer from interpenetration problems between the garment and the body.…
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…
LCollision: Fast Generation of Collision-Free Human Poses using Learned Non-Penetration Constraints
Qingyang Tan, Zherong Pan, Dinesh Manocha
We present LCollision, a learning-based method that synthesizes collision-free 3D human poses. At the crux of our approach is a novel deep architecture that simultaneously decodes…
DeepMNavigate: Deep Reinforced Multi-Robot Navigation Unifying Local & Global Collision Avoidance
Qingyang Tan, Tingxiang Fan, Jia Pan +1
We present a novel algorithm (DeepMNavigate) for global multi-agent navigation in dense scenarios using deep reinforcement learning (DRL). Our approach uses local and global inform…
Realtime Simulation of Thin-Shell Deformable Materials using CNN-Based Mesh Embedding
Qingyang Tan, Zherong Pan, Lin Gao +1
We address the problem of accelerating thin-shell deformable object simulations by dimension reduction. We present a new algorithm to embed a high-dimensional configuration space o…
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…