PointGT is a point-based 3D representation that allows simultaneous editing of both object geometry and appearance. Unlike volumetric 3D representations, which are hard to edit, PointGT combines a geometry-friendly point structure with a learned UV mapping for high-resolution texture editing. The method demonstrates fine-grained edits to geometry and texture while maintaining high rendering quality.
PointGT is a point-based 3D representation that allows simultaneous editing of both geometry and texture. It combines a point-based structure, which is well-suited for geometry deformations, with a learned UV mapping technique that supports high-resolution texture editing. The method demonstrates fine-grained editing capabilities while maintaining high rendering quality.
P-CORE introduces a self‑supervised surface consistency technique for point‑based neural representations, enabling robust adaptation to large deformations without needing ground‑truth deformed images. By generating random deformations and enforcing that the predicted surface after deformation matches the deformation applied to the original surface prediction, the method leverages attention‑based point representations with a learned interpolation kernel. Experiments on synthetic benchmarks and real‑world datasets show improved zero‑shot editing performance and reduced artifacts compared to existing point‑based approaches.
arXiv:2511.22228v3 Announce Type: replace-cross Abstract: Recent advancements in diffusion and flow models have greatly improved text-based image editing, yet methods that edit images independently o...
arXiv:2610.27049v1 Announce Type: new Abstract: Recent advances in unified visual editing have begun to consolidate image and video editing within a single model, while 3D scene editing remains large...
arXiv:2508.01684v2 Announce Type: replace Abstract: While diffusion models have demonstrated remarkable progress in 2D image generation and editing, extending these capabilities to 3D editing remains...
arXiv:2606. 07117v1 Announce Type: cross Abstract: This paper presents Native3D, the first end-to-end 3D scene generation framework that completely bypasses 2D intermediate representations.
arXiv:2607.07187v2 Announce Type: replace Abstract: Local editing of 3D objects remains a long-standing challenge. When interacting with 3D content, humans naturally tend to specify a coarse region o...
arXiv:2606. 05124v1 Announce Type: cross Abstract: After the success of 3D Gaussian Splatting (3DGS) for novel view synthesis, many works have explored how to also use it for geometric surface representation.
ArtNVG is a 3D stylization framework that uses reference style images to produce stylized 3D scenes with high reconstruction quality. Built on 3D Gaussian Splatting, it introduces Content‑Style Separated Control and Attention‑based Neighboring‑View Alignment to maintain local color and texture consistency across views. Experiments show that ArtNVG outperforms existing methods in content preservation, style alignment, and local consistency.
The paper introduces GaussianBlender, a feed‑forward framework that enables instant, high‑fidelity, geometry‑preserving, and multi‑view consistent 3D stylization driven by text. It learns disentangled latent spaces for geometry and appearance using spatially‑grouped 3D Gaussians, and applies a latent diffusion model for text‑conditioned edits. Evaluations demonstrate that GaussianBlender outperforms methods requiring per‑instance optimization, making scalable 3D stylization practical for large‑scale production.
arXiv:2609.23380v1 Announce Type: new Abstract: Gaussian Splatting has enabled real-time novel view synthesis, but its tightly coupled geometry and appearance representation often require a large num...
arXiv:2507. 11061v3 Announce Type: replace-cross Abstract: Recent advances in 3D neural representations and instance-level editing models have enabled the efficient creation of high-quality 3D content.