Edit4D is a new text‑to‑4D scene generation framework that builds editable 4D scenes by separately modeling background and dynamic characters. It decomposes user instructions into stage‑specific prompts for background, character, and composition, then uses text‑to‑image, camera‑conditioned priors, and image‑conditioned video priors to synthesize multi‑view images, reconstruct 3D Gaussian splatting backgrounds, animate characters into 4D meshes, and finally compose and refine the scene with text‑guided segmentation and contact‑aware optimization. This pipeline allows controllable camera motion, flexible object‑level editing, and practical construction of editable 4D scenes.
By Chanwoo Kim, Tackgeun You, Hwasup Lim
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...
By Yufeng Chi, Huimin Ma, Kafeng Wang, Jianmin Li
arXiv:2608.24169v1 Announce Type: new
Abstract: 3D geometry editing is a critical yet labor-intensive part of the graphics pipeline, requiring artists to translate creative intent into precise operat...
By Bo Pang, Jiaqi Pan, Xiaocheng Zhang, Jiacheng Xu, Guoping Wang, Peng-Shuai Wang
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...
By Youtan Yin, Yanning Zhou, Jiacheng Wei, Xiaofeng Yang, Jun Zhang, Jiayang Bai, Jingwen Ye, Weidong Zhang, Guosheng Lin
VINCIE‑NExT is a unified framework that transfers image editing capabilities to video editing by using in‑context visual demonstrations. It decomposes video editing into a chain of sub‑tasks (Video → Image → Image → Video), routing editing intent through the image domain and enabling joint training from heterogeneous image and video data under a single diffusion objective. The method introduces a novel position encoding to link image demonstrations and video frames, allowing pixel‑faithful appearance propagation, and supports test‑time scaling through progressive diffusion stages.
By Leigang Qu, Feng Cheng, Ziyan Yang, Bangbang Yang, Zhaoyang Huang, Wei Chow, Yicong Li, Wenjie Wang, Tat-Seng Chua, Yan Zeng
TASE introduces a truncation‑aware embedding space that projects pretrained 2D semantic features into 3D scene representations, allowing flexible and controllable editing. The method optimizes feature channels so that fewer channels yield abstract semantics while more channels preserve detail, and it enforces multi‑view consistency with a scale‑ and translation‑equivariant loss. A finetuning stage for the editing diffusion model further reduces artifacts from geometric changes, achieving competitive performance and outperforming prior methods on large‑scale geometric edits.
By Tim-Felix Faasch, Jochen Kall, Lucas Nunes, Jens Behley, Cyrill Stachniss
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.
By Josef Bengtson, Yaroslava Lochman, Fredrik Kahl
arXiv:2603. 03143v2 Announce Type: replace-cross Abstract: Leveraging the priors of 2D diffusion models for 3D editing has emerged as a promising paradigm.
By Jiyuan Wang, Chunyu Lin, Lei Sun, Zhi Cao, Yuyang Yin, Lang Nie, Zhenlong Yuan, Xiangxiang Chu, Yunchao Wei, Kang Liao, Guosheng Lin
Fine-grained control over continuous semantic attributes of 3D objects is essential for 3D content creation, but is not well supported by conventional 3D modeling workflows or prompt-based interaction...
While traditional graphics methods often synthesize 3D indoor scenes autoregressively or hierarchically, recent vision-language model (VLM)-based generators predominantly adopt a one-shot paradigm where the full layout is planned at once. This one-shot approach often requires global re-optimization or complete reconstruction during interactive editing (e.
arXiv:2608.18560v2 Announce Type: replace-cross
Abstract: Fine-grained control over continuous semantic attributes of 3D objects is essential for 3D content creation, but is not well supported by con...
By Ru Wang, Rahul Jain, Koichiro Niinuma, Aakar Gupta
arXiv:2608.21438v1 Announce Type: new
Abstract: Text guided 3D scene editing provides an intuitive interface for modifying reconstructed environments, but remains difficult because natural language d...
By Xiujin Liu, Tianyu Yang, Yilun Zhao, Xiangliang Zhang