Diffusion-Based Generation of Gait Trajectories

arXiv:2604.09035v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) with autoregressive world models suffers from compounding errors, whereas diffusion world

arXiv:2603.25283v1 Announce Type: new Abstract: Gait is increasingly recognized as a vital sign, yet current approaches treat it as a symptom of specific pathologies rather than a

arXiv:2606.19935v1 Announce Type: new Abstract: Humanoid robots require co-speech motions that are not only expressive and speech-aligned, but also physically executable under

arXiv:2607.20545v1 Announce Type: new Abstract: Diffusion models have become competitive generators for time series, but their practical use is limited by the large number of

arXiv:2604.05394v1 Announce Type: new Abstract: Physics-based character animation has become a fundamental approach for synthesizing realistic, physically plausible motions. While

arXiv:2603.18979v1 Announce Type: cross Abstract: Training perceptive humanoid locomotion policies that traverse complex terrains with natural gaits remains an open challenge,