Mono4DEditor：通过语言嵌入高斯的点级定位实现基于文本的单目视频4D场景编辑
Mono4DEditor: Text-Driven 4D Scene Editing from Monocular Video via Point-Level Localization of Language-Embedded Gaussians
AI总结：
提出Mono4DEditor框架，利用语言嵌入高斯和两阶段点级定位，结合扩散模型实现单目视频4D场景的精确文本驱动编辑，保持未编辑区域完整性并超越现有方法。
摘要：
基于文本提示编辑从单目视频重建的4D场景是一项有价值但具有挑战性的任务，在内容创作和虚拟环境中具有广泛的应用。关键难点在于在复杂动态场景的局部区域实现语义精确的编辑，同时保持未编辑内容的完整性。为解决这一问题，我们提出了Mono4DEditor，一个用于灵活且精确的文本驱动4D场景编辑的新框架。我们的方法将3D高斯与量化CLIP特征相结合，形成语言嵌入的动态表示，从而能够对任意空间区域进行高效的语义查询。我们进一步提出了一种两阶段点级定位策略，首先通过CLIP相似性选择候选高斯，然后细化其空间范围以提高准确性。最后，使用基于扩散的视频编辑模型对局部区域进行定向编辑，并通过光流和涂鸦引导确保空间保真度和时间一致性。大量实验表明，Mono4DEditor能够在多样场景和对象类型上实现高质量的文本驱动编辑，同时保持未编辑区域的外观和几何形状，并在灵活性和视觉保真度方面超越先前方法。
英文摘要：
Editing 4D scenes reconstructed from monocular videos based on text prompts is a valuable yet challenging task with broad applications in content creation and virtual environments. The key difficulty lies in achieving semantically precise edits in localized regions of complex, dynamic scenes, while preserving the integrity of unedited content. To address this, we introduce Mono4DEditor, a novel framework for flexible and accurate text-driven 4D scene editing. Our method augments 3D Gaussians with quantized CLIP features to form a language-embedded dynamic representation, enabling efficient semantic querying of arbitrary spatial regions. We further propose a two-stage point-level localization strategy that first selects candidate Gaussians via CLIP similarity and then refines their spatial extent to improve accuracy. Finally, targeted edits are performed on localized regions using a diffusion-based video editing model, with flow and scribble guidance ensuring spatial fidelity and temporal coherence. Extensive experiments demonstrate that Mono4DEditor enables high-quality, text-driven edits across diverse scenes and object types, while preserving the appearance and geometry of unedited areas and surpassing prior approaches in both flexibility and visual fidelity.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
