MATE4D is a framework that transforms a single image into editable dynamic 4D content. It builds a spatio-temporal multi-view image matrix with text-guided background manipulation, then optimizes 3D Gaussian primitives and animates them with a lightweight deformation module. The approach yields scenes with more faithful geometry, smoother temporal behavior, and consistent background edits, outperforming baselines on Objaverse-XL and Diffusion4D.
By Xiaotian Chen, Dongfu Yin
The paper introduces Chat-Edit-3D++ (CE3D++), an interactive 3D and 4D scene editing system that uses a Hash-Atlas network to separate 2D editing from 3D reconstruction. CE3D++ employs a large language model to accept arbitrary textual input, interpret user intent, and autonomously invoke appropriate visual models, enabling multi‑round dialogue and diverse editing effects. The approach is extended to monocular 4D scenes by adding motion constraints and a trajectory dataset, allowing a smaller LLM to schedule up to 30 visual tools accurately.
By Shuangkang Fang, Yufeng Wang, Yi-Hsuan Tsai, Wenrui Ding, Yi Yang, Shuchang Zhou, Ming-Hsuan Yang
4DSynth is a controllable procedural system that transforms natural-language descriptions, blueprint masks, or single photographs into editable 4D environments featuring explicit geometry, animated actors, collision-free trajectories, and physics-ready simulation states. The system unifies animation, camera planning, rendering, and task generation within a single geometry-grounded representation, enabling scalable creation of dynamic embodied simulation scenes. Using 4DSynth, the authors built 4DSynth-Nav, an interactive navigation benchmark that demonstrates the reproducibility and tunability of procedural failures across vision‑language models.
By Zehao Qi, Haochen Luo, Jia-Wang Bian, Zeyu Ma, Shuyang Sun
arXiv:2607. 01766v1 Announce Type: new Abstract: LLM agents are increasingly used to translate natural language into 3D scenes in a procedural way, but existing systems focus on static output.
By Chunjiang Liu, Xiaoyuan Wang, Haoyu Chen, Yizhou Zhao, Ming-Hsuan Yang, L\'aszl\'o A. Jeni
LLM agents are increasingly used to translate natural language into 3D scenes in a procedural way, but existing systems focus on static output. Dynamic 4D scenes from text alone, in which liquids flow, particles emit, rigid bodies cascade, and articulated mechanisms move, remain largely unexplored despite their value as editable content and as physics-grounded training data for video generation and embodied AI.
arXiv:2608.18734v2 Announce Type: replace
Abstract: 4D understanding and reasoning is a fundamental capability for embodied AI agents operating in dynamic physical environments. However, existing vis...
By Kumal Hewagamage, Isuranga Senavirathne, Sasika Amarasinghe, Hasitha Gallella, Dulanga Weerakoon, Vigneshwaran Subbaraju, Ranga Rodrigo