From the 1 of 3 linked papers with an AI index.
3 papers
cs.CV2026
MoLingo: Motion-Language Alignment for Text-to-Human Motion Generation
Yannan He, Garvita Tiwari, Xiaohan Zhang +4
MoLingo is a model that generates realistic human motion from textual descriptions by using a semantically aligned latent space and cross‑attention conditioning during diffusion.
cs.CV2026
ActionPlan: Future-Aware Streaming Motion Synthesis via Frame-Level Action Planning
Eric Nazarenus, Chuqiao Li, Yannan He +3
We present ActionPlan, a unified motion diffusion framework that bridges real-time streaming with high-quality offline generation within a single model. The core idea is to introdu…
cs.CV2024
Unimotion: Unifying 3D Human Motion Synthesis and Understanding
Chuqiao Li, Julian Chibane, Yannan He +3
We introduce Unimotion, the first unified multi-task human motion model capable of both flexible motion control and frame-level motion understanding. While existing works control a…