Dongze Wu

GazeDiT is introduced, a diffusion model that generates images for a requested 4D gaze through an internally constructed spatial condition that grounds the global gaze label in this local geometry, and achieves substantially lower tail gaze-label error than other diffusion baselines.

Learning generative models for high-dimensional matrices doesn't have to be a computational nightmare: CoreFlow achieves state-of-the-art results in low-data regimes by learning shared low-rank structure.