We present GSEdit, a pipeline for text-guided 3D object editing based on Gaussian Splatting models. Our method enables the editing of the style and appearance of 3D objects without altering their main details, all in a matter of minutes on consumer hardware. We tackle the problem by leveraging Gaussian splatting to represent 3D scenes, and we optimize the model while progressively varying the image supervision by means of a pretrained image-based diffusion model. The input object may be given as a 3D triangular mesh, or directly provided as Gaussians from a generative model such as DreamGaussian. GSEdit ensures consistency across different viewpoints, maintaining the integrity of the original object's information. Compared to previously proposed methods relying on NeRF-like MLP models, GSEdit stands out for its efficiency, making 3D editing tasks much faster. Our editing process is refined via the application of the SDS loss, ensuring that our edits are both precise and accurate. Our comprehensive evaluation demonstrates that GSEdit effectively alters object shape and appearance following the given textual instructions while preserving their coherence and detail.

翻译：我们提出GSEdit——一种基于高斯泼溅模型的文本引导3D对象编辑流水线。该方法可在消费级硬件上数分钟内完成3D对象风格与外观的编辑，同时保留其核心细节。我们通过高斯泼溅表示3D场景，并利用预训练图像扩散模型逐步调整图像监督信号来优化模型。输入对象既可以是3D三角网格，也可以是来自DreamGaussian等生成模型的高斯表示。GSEdit确保多视角一致性，维持原始对象信息的完整性。与以往依赖NeRF类MLP模型的方法相比，GSEdit凭借其高效性脱颖而出，大幅加速了3D编辑任务。通过应用SDS损失优化编辑过程，确保编辑操作的精准可靠。综合评估表明，GSEdit能根据文本指令有效改变对象形状与外观，同时保持其连贯性与细节特征。