2 citations · 3 across the 4 of their papers we have counts for
5 papers
TEDi: Temporally-Entangled Diffusion for Long-Term Motion Synthesis
Zihan Zhang, Richard Liu, Kfir Aberman +1
The gradual nature of a diffusion process that synthesizes samples in small increments constitutes a key ingredient of Denoising Diffusion Probabilistic Models (DDPM), which have p…
DA Wand: Distortion-Aware Selection using Neural Mesh Parameterization
Richard Liu, Noam Aigerman, Vladimir G. Kim +1
We present a neural technique for learning to select a local sub-region around a point which can be used for mesh parameterization. The motivation for our framework is driven by in…
A neural net architecture based on principles of neural plasticity and development evolves to effectively catch prey in a simulated environment
Addison Wood, Jory Schossau, Nick Sabaj +2
A profound challenge for A-Life is to construct agents whose behavior is 'life-like' in a deep way. We propose an architecture and approach to constructing networks driving artific…
Text2Mesh: Text-Driven Neural Stylization for Meshes
Oscar Michel, Roi Bar-On, Richard Liu +2
In this work, we develop intuitive controls for editing the style of 3D objects. Our framework, Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which…
A Scalable and Cloud-Native Hyperparameter Tuning System
Johnu George, Ce Gao, Richard Liu +4
In this paper, we introduce Katib: a scalable, cloud-native, and production-ready hyperparameter tuning system that is agnostic of the underlying machine learning framework. Though…