71 citations · 162 across the 4 of their papers we have counts for
11 papers
Driving-Signal Aware Full-Body Avatars
Timur Bagautdinov, Chenglei Wu, Tomas Simon +6
We present a learning-based method for building driving-signal aware full-body avatars. Our model is a conditional variational autoencoder that can be animated with incomplete driv…
Modeling Clothing as a Separate Layer for an Animatable Human Avatar
Donglai Xiang, Fabian Prada, Timur Bagautdinov +5
We have recently seen great progress in building photorealistic animatable full-body codec avatars, but generating high-fidelity animation of clothing is still difficult. To addres…
MonoClothCap: Towards Temporally Coherent Clothing Capture from Monocular RGB Video
Donglai Xiang, Fabian Prada, Chenglei Wu +1
We present a method to capture temporally coherent dynamic clothing deformation from a monocular RGB video input. In contrast to the existing literature, our method does not requir…
Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels
Yi Zhou, Chenglei Wu, Zimo Li +5
Learning latent representations of registered meshes is useful for many 3D tasks. Techniques have recently shifted to neural mesh autoencoders. Although they demonstrate higher pre…
Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning
Xin Yao, Tianchi Huang, Chenglei Wu +2
Human beings are able to master a variety of knowledge and skills with ongoing learning. By contrast, dramatic performance degradation is observed when new tasks are added to an ex…
Federated Learning with Additional Mechanisms on Clients to Reduce Communication Costs
Xin Yao, Tianchi Huang, Chenglei Wu +2
Federated learning (FL) enables on-device training over distributed networks consisting of a massive amount of modern smart devices, such as smartphones and IoT (Internet of Things…