Part-aware 3D generation aims to create digital assets that are coherent as complete objects while exposing structural parts for editing, material assignment, animation, and reuse. Existing methods impose this structure outside the native generation loop: segmentation-based methods partition an already generated shape, while additive methods synthesize parts from predefined layouts, boxes, or tokens and then reconcile them into a whole.
arXiv:2608.20448v1 Announce Type: cross
Abstract: Digital 3D objects used in games and animation are often required to be compositional; that is, decomposed into semantically meaningful parts. Recent...
By Ava Pun, Kangle Deng, Yiheng Zhu, Jun-Yan Zhu, Maneesh Agrawala, Tinghui Zhou
KaiNinja extends the native 3D generator TRELLIS.2 to produce part-level meshes by introducing a dual‑volume representation that overcomes the single‑sheet limitation of the O‑Voxel grid. It maintains TRELLIS.2’s speed and quality while eliminating the need for external segmentation, and is trained on diverse data including CAD models and assets created by an LLM‑driven agent. The method improves whole‑object fidelity and outperforms other part‑generation pipelines, reducing Chamfer distance by 40% and increasing strict part F‑score by 16%.
By Ruihan Yu, Lian Fu, Muyao Niu, Zheng-hui Huang, Yu-Ju Tsai, Sho Kuno, Fengbo Lan, Yonghao Yu, Erwin Wu, Ming-Hsuan Yang, Kaipeng Zhang, Zhixiang Wang
arXiv:2609.15659v1 Announce Type: cross
Abstract: Native 3D generators turn one image into a single mesh. TRELLIS.2 and its peers deliver high-fidelity non-watertight geometry with materials, but the...
By Ruihan Yu, Lian Fu, Muyao Niu, Zheng-hui Huang, Yu-Ju Tsai, Sho Kuno, Fengbo Lan, Yonghao Yu, Erwin Wu, Ming-Hsuan Yang, Kaipeng Zhang, Zhixiang Wang
arXiv:2606. 08402v2 Announce Type: replace-cross Abstract: Generating complete 3D scenes from a single image requires inferring globally consistent geometry, object relationships, and environmental context from inherently ambiguous visual evidence.
By Jeonghwan Kim, Yushi Lan, Yongwei Chen, Hieu Trung Nguyen, Chuanyu Pan, Xingang Pan
Part-level 3D generation has recently attracted increasing attention for producing structured and editable 3D assets. However, existing methods typically decompose objects according to functional semantics rather than the editable material boundaries (e.
arXiv:2606. 08402v1 Announce Type: cross Abstract: Generating complete 3D scenes from a single image requires inferring globally consistent geometry, object relationships, and environmental context from inherently ambiguous visual evidence.
By Jeonghwan Kim, Yushi Lan, Yongwei Chen, Hieu Trung Nguyen, Chuanyu Pan, Xingang Pan
arXiv:2603. 16085v2 Announce Type: replace-cross Abstract: Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets.
By Hui Shan, Keyang Luo, Ming Li, Sizhe Zheng, Yanwei Fu, Zhen Chen, Xiangru Huang
WorldSculpt presents a method for generating compositional 3D representations of cluttered scenes with hundreds of objects by adapting a single-object 3D generative prior to multi-view observations. The approach, built on Pixal3D with a multi-view conditioning pathway, can generalize to highly occluded scenes without scene-level training. The authors also introduce the UE-MeshyScene benchmark and demonstrate that their method outperforms prior approaches across various evaluation settings, including converting existing 3DGS worlds into compositional mesh scenes.
By Muyao Niu, Jixuan He, Ruihan Yu, Lian Fu, Yonghao Yu, Zheng-Hui Huang, Yifan Zhan, Fengbo Lan, Yongtao Ge, Yinqiang Zheng, Kaipeng Zhang, Zhixiang Wang
Artic-O is an end‑to‑end, feed‑forward framework that reconstructs articulated objects from sparse images by learning latent geometry. It maps multi‑state observations into a pretrained latent geometry space, uses a frozen flow‑matching decoder for complete‑shape priors, and fuses visual tokens with geometry latents in an image‑grounded part‑reasoning module to segment active parts and predict articulation. Trained with a geometry‑to‑articulation curriculum and a decoupled two‑pass strategy, Artic‑O achieves high reconstruction quality and articulation accuracy while drastically reducing inference time from 9 minutes to about 0.3 seconds per object.
By Xuyang Wang, Zhenyu Li, Jian Ding, Habib Slim, Peter Wonka, Hongdong Li, Mohamed Elhoseiny
arXiv:2605. 19350v2 Announce Type: replace-cross Abstract: Creating and editing high-quality 3D content remains a central challenge in computer graphics.
By Habib Slim, Shariq Farooq Bhat, Mohamed Elhoseiny, Yifan Wang, Mike Roberts
SceneReGen is a new framework for reconstructing 3D scenes from a single image by generating and assembling complete object meshes within a shared observation‑aligned scene frame. It uses selective pose factorization to encode each object’s observed orientation directly into the generated mesh, while estimating translation and scale from instance‑level and global scene cues. Evaluated on the 3D‑FUTURE dataset, SceneReGen outperforms existing methods on scene‑level metrics and shows strong performance on object‑level metrics, demonstrating its effectiveness in autonomous‑driving and embodied‑AI scenarios.
By Zefan Tian, Yuteng Ye, Yiheng Zhang, Yuhang Yang, Xueqiang Lv, Shizhou Zhang, Le Liu, Di Xu