7 accepted papers
The authentic 3D hand avatar with every identifiable information such as hand shapes and textures is necessary for immersive experiences in AR/VR. In this paper we present a universal hand model (UHM) which 1) can universally represent high-fidelity 3D hand meshes of arbitrary identities (IDs) and 2…
"We present Neural Strands, a novel learning framework for modeling accurate hair geometry and appearance from multi-view image inputs. The learned hair model can be rendered in real-time from any viewpoint with high-fidelity view-dependent effects. Our model achieves intuitive shape and style contr…
Learning latent representations of registered meshes is useful for many 3D tasks. Techniques have recently shifted to neural mesh autoencoders. Although they demonstrate higher precision than traditional methods, they remain unable to capture fine-grained deformations. Furthermore, these methods can…
Hair is one of the most challenging objects to reconstruct due to its micro-scale structure and a large number of repeated strands with heavy occlusions. In this paper, we present the first method to capture high-fidelity hair geometry with strand-level accuracy. Our method takes three stages to ach…
Consumer depth sensors are more and more popular and come to our daily lives marked by its recent integration in the latest Iphone X. However, they still suffer from heavy noises which limit their applications. Although plenty of progresses have been made to reduce the noises and boost geometric det…
We present an approach to accelerate multi-view stereo (MVS) by prioritizing computation on image patches that are likely to produce accurate 3D surface reconstructions. Our key insight is that the accuracy of the surface reconstruction from a given image patch can be predicted significantly faster…
We propose a method for learning non-linear face geometry representations using deep generative models. Our model is a variational autoencoder with multiple levels of hidden variables where lower layers capture global geometry and higher ones encode more local deformations. Based on that, we pr…