Tianyu Shen

4DWeaver: Bridging Reconstruction and Generation Via Compact Autoregressive Priors.

This work proposes Compact Autoregressive Latent Prior (CALP), which regularizes low-dimensional latent variables with a history-conditioned autoregressive prior, achieving compact, long-range temporally coherent, and spatially structured latent representations through a more reasonable latent capacity allocation and a latent-space organization that is better suited for diffusion-based 4D generation.