SOURCE-LINKED INTELLIGENCE
RoGe: Novel View Synthesis via End-to-End Implicit Reconstruction and Generation
Novel view synthesis from sparse inputs requires both geometric grounding from the observed views and generative priors of unobserved regions, motivating recent hybrid methods that combine reconstruction and generation. However, existing methods bridge the two with rendered images or explicit 3D representations such as point maps or 3D Gaussians. Generation is thus conditioned on a lossy and imperfect projection of the scene, inheriting its errors, and reconstruction receives no signal from generation to correct them. We present RoGe, an end-to-end unified reconstruction and generation framewo
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T17:32:35.000Z
First collected: 2026-09-21T05:11:56.580Z. This is not the publication date.