Text-driven 3D scene editing has gained significant attention owing to its convenience and user-friendliness. However, existing methods still lack accurate control of the specified appearance and location of the editing result due to the inherent limitations of the text description. To this end, we propose a 3D scene editing framework, TIPEditor, that accepts both text and image prompts and a 3D bounding box to specify the editing region. With the image prompt, users can conveniently specify the detailed appearance/style of the target content in complement to the text description, enabling accurate control of the appearance. Specifically, TIP-Editor employs a stepwise 2D personalization strategy to better learn the representation of the existing scene and the reference image, in which a localization loss is proposed to encourage correct object placement as specified by the bounding box. Additionally, TIPEditor utilizes explicit and flexible 3D Gaussian splatting as the 3D representation to facilitate local editing while keeping the background unchanged. Extensive experiments have demonstrated that TIP-Editor conducts accurate editing following the text and image prompts in the specified bounding box region, consistently outperforming the baselines in editing quality, and the alignment to the prompts, qualitatively and quantitatively.

翻译：文本驱动的三维场景编辑因其便捷性和用户友好性而受到广泛关注。然而，由于文本描述的固有局限性，现有方法在编辑结果的具体外观和位置控制方面仍缺乏精确性。为此，我们提出了一种三维场景编辑框架TIP-Editor，该框架同时接受文本和图像提示，并通过三维边界框指定编辑区域。借助图像提示，用户可以方便地在文本描述基础上补充指定目标内容的详细外观/风格，从而实现对外观的精确控制。具体而言，TIP-Editor采用逐步二维个性化策略，以更好地学习现有场景和参考图像的表示，其中引入定位损失以鼓励按边界框指定位置正确放置物体。此外，TIP-Editor利用显式且灵活的三维高斯喷洒作为三维表示，便于在保持背景不变的情况下进行局部编辑。大量实验表明，TIP-Editor能在指定边界框区域内遵循文本和图像提示进行精确编辑，在编辑质量及提示对齐度方面始终优于基线方法，定性及定量结果均验证了其有效性。