Kaininja: Extending Native 3D Generators to the Part Level
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
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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%.
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:2609.15639v1 Announce Type: new Abstract: Part-level control is essential for modern 3D asset creation, where objects are frequently edited, reused, animated, or fabricated through their indivi...
STRUCTPARTS is a new framework that reuses holistic 3D priors to generate part‑decomposed 3D assets. It introduces a dual‑frame coordinate interleaving mechanism, interpreting each shape latent under both part‑local and object‑global reference frames and processing them with a global‑local inter‑leaved transformer. Using a segmented mesh scaffold as structural input, the method achieves detailed intra‑part geometry and coherent inter‑part structure with lightweight finetuning, outperforming prior part‑decomposed models on PartObjaverse‑Tiny while enabling part‑mesh refinement and editing.
arXiv:2609.38180v1 Announce Type: new Abstract: Existing 3D part decomposition methods do not necessarily partition the original shape into non-overlapping parts that collectively cover the entire sh...
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.