6 papers · 1 filter
GeM-NR: Geometry-Aware Multi-View Editing for Nonrigid Scene Changes
Josef Bengtson, Yaroslava Lochman, Fredrik Kahl
Recent developments in multi-view image editing with generative models have brought us a step closer toward general 3D content generation and customization. Most existing works foc…
Matryoshka Gaussian Splatting
Zhilin Guo, Boqiao Zhang, Hakan Aktas +11
The ability to render scenes at adjustable fidelity from a single model, known as level of detail (LoD), is crucial for practical deployment of 3D Gaussian Splatting (3DGS). Existi…
3D-Consistent Multi-View Editing by Correspondence Guidance
Josef Bengtson, David Nilsson, Dong In Lee +2
Recent advancements in diffusion and flow models have greatly improved text-based image editing, yet methods that edit images independently often produce geometrically and photomet…
Geometric Consistency Refinement for Single Image Novel View Synthesis via Test-Time Adaptation of Diffusion Models
Josef Bengtson, David Nilsson, Fredrik Kahl
Diffusion models for single image novel view synthesis (NVS) can generate highly realistic and plausible images, but they are limited in the geometric consistency to the given rela…
FlowIBR: Leveraging Pre-Training for Efficient Neural Image-Based Rendering of Dynamic Scenes
Marcel Büsching, Josef Bengtson, David Nilsson +1
We introduce FlowIBR, a novel approach for efficient monocular novel view synthesis of dynamic scenes. Existing techniques already show impressive rendering quality but tend to foc…
Adjustable Visual Appearance for Generalizable Novel View Synthesis
Josef Bengtson, David Nilsson, Che-Tsung Lin +2
We present a generalizable novel view synthesis method which enables modifying the visual appearance of an observed scene so rendered views match a target weather or lighting condi…