arXiv Artificial Intelligence

UniQueR: Unified Query-based Feedforward 3D Reconstruction

1 day ago 10.09.2026 07:00 👁 1 views
UniQueR: Unified Query-based Feedforward 3D Reconstruction

Quick summary

arXiv:2603.22851v2 Announce Type: replace-cross Abstract: We present UniQueR, a unified query-based feedforward framework for efficient and accurate 3D reconstruction from unposed images. Existing feedforward models such as DUSt3R, VGGT, and AnySplat typically predict per-pixel point maps or pixel-aligned Gaussians, which remain fundamentally 2.5D and limited to visible surfaces. In contrast, UniQueR formulates reconstruction as a sparse 3D query inference problem. Our model learns a compact set of 3D anchor points that act as explicit geometric queries, enabling the network to infer scene str

Key takeaways

  • arXiv:2603.22851v2 Announce Type: replace-cross Abstract: We present UniQueR, a unified query-based feedforward framework for efficient and accurate 3D reconstruction from unposed images.
  • Existing feedforward models such as DUSt3R, VGGT, and AnySplat typically predict per-pixel point maps or pixel-aligned Gaussians, which remain fundamentally 2.5D and limited to visible surfaces.
  • In contrast, UniQueR formulates reconstruction as a sparse 3D query inference problem.

Why it matters

“UniQueR: Unified Query-based Feedforward 3D Reconstruction” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗