4D-Editor: Interactive Object-Level Editing in Dynamic Neural Radiance Fields via Semantic Distillation
Year: 2025
Type: conference-paper
Abstract: This paper targets interactive object-level editing (e.g., deletion, recoloring, transformation, composition) in dynamic scenes. Recently, some methods aiming for flexible editing static scenes represented by neural radiance field (NeRF) have shown impressive synthesis quality, while similar capabilities in time-variant dynamic scenes remain limited. To solve this problem, we propose 4D-Editor, an interactive semantic-driven editing framework, allowing editing multiple objects in a dynamic NeRF with user strokes on a single frame. Specifically, we extend the original dynamic NeRF by incorporating Hybrid Semantic Feature Distillation to maintain spatial-temporal consistency after editing. In addition, a Recursive Selection Refinement module is presented to significantly boost object segmentation accuracy within a dynamic NeRF to aid the editing process. Moreover, we develop Multi-view Reprojection Inpainting to fill holes caused by incomplete scene capture after editing. Extensive quantitative and qualitative experiments on real application scenarios demonstrate that 4D-Editor achieves photo-realistic editing on dynamic NeRFs. Project page: https://patrickddj.github.ioI/4D-Editor
Institution: Tianjin University
Language: English
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4413557100