3 papers
cs.CV2026
Spatiotemporally Decoupled Autoregressive Diffusion Model for Human Motion Generation
Chengqun Yang, Liang Xu, Yanping Li +4
Text-driven human motion synthesis has made substantial development with two core modules of motion representation and generative architecture. For representation, Vector Quantizat…
cs.CV2026
MRBench: A Comprehensive Benchmark for Human Motion-Text Retrieval
Fulong Liu, Liang Xu, Chengqun Yang +3
Human motion-text retrieval provides a rigorous means of assessing cross-modal alignment. Prevailing benchmarks are dominated by homogeneous indoor motions, imbalanced motion distr…
cs.RO2026
Enfold: Folding World Model Imagination into Predictive Representations for Ultra-Efficient Embodied Control
Weili Zeng, Yitong Xing, Fulong Liu +10
World generative models are typically used through what they produce: a rendered future, a video-conditioned action, or latent context computed by a costly generative branch. We ar…