In the real world, objects reveal internal textures when sliced or cut, yet this behavior is not well-studied in 3D generation tasks today. For example, slicing a virtual 3D watermelon should reveal flesh and seeds. Given that no available dataset captures an object's full internal structure and collecting data from all slices is impractical, generative methods become the obvious approach. However, current 3D generation and inpainting methods often focus on visible appearance and overlook internal textures. To bridge this gap, we introduce FruitNinja, the first method to generate internal textures for 3D objects undergoing geometric and topological changes. Our approach produces objects via 3D Gaussian Splatting (3DGS) with both surface and interior textures synthesized, enabling real-time slicing and rendering without additional optimization. FruitNinja leverages a pre-trained diffusion model to progressively inpaint cross-sectional views and applies voxel-grid-based smoothing to achieve cohesive textures throughout the object. Our OpaqueAtom GS strategy overcomes 3DGS limitations by employing densely distributed opaque Gaussians, avoiding biases toward larger particles that destabilize training and sharp color transitions for fine-grained textures. Experimental results show that FruitNinja substantially outperforms existing approaches, showcasing unmatched visual quality in real-time rendered internal views across arbitrary geometry manipulations.
在现实世界中，物体被切开或分割时会显露其内部纹理，但这一行为在当前的3D生成任务中并未得到充分研究。例如，切开一个虚拟的3D西瓜应显示其果肉和种子。然而，目前没有可用的数据集能够捕获物体的完整内部结构，同时从所有切片收集数据也不现实，因此生成式方法成为显而易见的解决方案。然而，当前的3D生成与修补方法通常关注物体的可见外观，而忽略了内部纹理。 为弥补这一空白，我们提出 FruitNinja，这是首个针对几何和拓扑变化生成3D物体内部纹理的方法。我们的方法通过 3D Gaussian Splatting (3DGS) 生成物体，合成表面与内部纹理，实现实时切割和渲染，无需额外的优化过程。FruitNinja 利用预训练的扩散模型逐步修补横截面视图，并通过基于体素网格的平滑方法生成物体内部一致的纹理。 此外，我们提出了 OpaqueAtom GS 策略，克服了 3DGS 的局限性。该策略采用密集分布的不透明高斯点，避免了对较大粒子的偏向，这些偏向通常会导致训练不稳定及颜色过渡不够精细的问题，从而实现了细腻的纹理效果。实验结果表明，FruitNinja 在实时渲染的内部视图质量上远超现有方法，在任意几何操作下展现了无与伦比的视觉效果。