RADI3N is a new framework for part‑level image editing that provides parametric 3D control. It introduces a CS‑ARAP deformation module that smooths rotation discontinuities at part boundaries, and an inversion‑free selective texture transfer mechanism that reduces positional bias and enhances semantic matching. The method achieves state‑of‑the‑art results in geometric fidelity, viewpoint consistency, and controllability.
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:2605. 19350v2 Announce Type: replace-cross Abstract: Creating and editing high-quality 3D content remains a central challenge in computer graphics.
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:2606.13345v2 Announce Type: replace Abstract: Existing 3D scene editing methods typically rely on per-scene optimization over explicit 3D representations or cascaded edit-and-reconstruct pipeli...
arXiv:2603. 16085v2 Announce Type: replace-cross Abstract: Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets.
arXiv:2606. 27584v1 Announce Type: cross Abstract: 3D scene inpainting is essential for reconstructing areas corrupted by occlusions or limited viewpoints.
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.
Generative Cinematographer (GenCine) lifts a single image into an editable 3D scene scaffold, allowing artists to jointly author camera paths and foreground motion using local 3D motion handles. The system projects these controls into guidance maps that encode handle positions and colors across frames, enabling a pretrained video model to follow camera-relative, piecewise-rigid motion without physics simulation. Training recovers controls from real videos and synthetic ground-truth geometry, and experiments demonstrate consistent camera-relative motion, improved geometric consistency, and strong controllability across diverse real-world scenes.
arXiv:2610.35756v1 Announce Type: new Abstract: Recent advancements in text-guided 3D editing, particularly with 3D Gaussian Splatting (3DGS), have shown promise but still lag behind the flexibility...
arXiv:2603. 03143v2 Announce Type: replace-cross Abstract: Leveraging the priors of 2D diffusion models for 3D editing has emerged as a promising paradigm.
arXiv:2606. 05142v1 Announce Type: cross Abstract: Recent developments in multi-view image editing with generative models have brought us a step closer toward general 3D content generation and customization.
arXiv:2611.07922v1 Announce Type: new Abstract: Text-guided image editing with diffusion models struggles with spatial edits (e.g. manipulating objects, changing viewpoints, manipulating occlusions)...