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arXiv:2609.09890v1 Announce Type: new Abstract: Multi-view diffusion models have shown strong performance in scenes with strong geometric priors and sparse semantics, such as indoor rooms or simple o...
MeSS (Mesh-based Scene Synthesis) is a method that generates high‑quality, style‑consistent outdoor scenes using city mesh models as geometric priors. The pipeline first creates geometrically consistent sparse views with Cascaded Outpainting ControlNets, then densifies intermediate views via AGInpaint, and finally removes visual inconsistencies with GCAlign. Simultaneously, a 3D Gaussian Splatting scene is reconstructed from the mesh, enabling diverse rendering styles after synthesis.
GroundControl introduces a satellite‑conditioned multi‑view diffusion model for novel view synthesis that uses satellite images alongside street‑level inputs. The cross‑attention conditioning preserves pretrained diffusion priors while ensuring realistic spatial layouts, even when target views have little overlap with source views. Experiments on outdoor datasets demonstrate superior performance over both satellite‑only and street‑only baselines without relying on 3D reconstruction.
GroundControl introduces a satellite-conditioned multi‑view diffusion model for novel view synthesis that leverages both satellite imagery and street‑level inputs. The approach uses cross‑attention conditioning to preserve pretrained diffusion priors while aligning generated views with the scene layout seen from satellite images, avoiding unrealistic hallucinations. Experiments on outdoor datasets demonstrate superior performance over baselines, particularly when target views have minimal overlap with source views.
The paper introduces ESC, a framework that improves 3D-consistent novel view synthesis from a single 2D image by jointly generating a target view and its depth map. By conditioning the diffusion model on the source image, source depth, and target camera rays, ESC forces the model to reason in 3D even under extreme viewpoint changes. A per‑pixel depth consistency constraint is added to enforce spatial fidelity, resulting in superior visual accuracy and spatial alignment compared to current state‑of‑the‑art methods.
arXiv:2607. 00832v1 Announce Type: cross Abstract: A single panorama captures the full visual sphere from one camera center, yet confines users to looking around in place without enabling true scene exploration.