2 papers
cs.CV2026
Riemannian Motion Generation: A Unified Framework for Human Motion Representation and Generation via Riemannian Flow Matching
Fangran Miao, Jian Huang, Ting Li
Human motion generation is often learned in Euclidean spaces, although valid motions follow structured non-Euclidean geometry. We present Riemannian Motion Generation (RMG), a unif…
stat.ML2025
Conditional Stochastic Interpolation for Generative Learning
Ding Huang, Jian Huang, Ting Li +1
We propose a conditional stochastic interpolation (CSI) method for learning conditional distributions. CSI is based on estimating probability flow equations or stochastic different…