Stream3D: Sequential Multi-View 3D Generation via Evidential Memory 事件

Stream3D: Sequential Multi-View 3D Generation via Evidential Memory arXiv:2605.21472v2 Announce Type: replace Abstract: View-conditioned 3D generators such as SAM 3D, TRELLIS, and Hunyuan3D produce high-quality object reconstructions from a single view, but real-world visual observation often arrives as long monocular streams. Naively applying these generators to each streaming frame independently leads to severe temporal inconsistency in the generated results. To address this problem, we propo