TRACE: Transient Recognition, Authentication, and Coverage-aware Editing

Recent advances in 3D Gaussian Splatting (GS) have enabled high-quality novel view synthesis from casually captured images, yet fully automatic transient object removal remains challenging. Existing methods rely on unreliable geometric cues or assume accurate transient masks are available, often removing persistent objects that belong to transient semantic categories. We present TRACE, a fully automatic pipeline that authenticates transient objects before editing. Candidate objects are detected using off-the-shelf instance segmentation and verified through multi-view geometric persistence derived from Structure-from-Motion, with cross-view semantic consistency resolving ambiguous cases. Using the authenticated masks, TRACE selects a minimal yet informative set of views for diffusion-based inpainting by jointly optimizing geometric coverage and object visibility. Experiments on challenging real-world datasets demonstrate that TRACE significantly improves transient localization and produces higher-quality Gaussian Splatting reconstructions than existing geometry- and category-based approaches.