He, Xiaosheng, Liu, Fenglin, Gao, Lin, Lai, YuKun  ORCID: https://orcid.org/0000-0002-2094-5680, Cai, Zhongang, Yang, Lei, Xu, Yi and Lin, Guosheng
2026.
Consistent 4D appearance editing with Gaussian Splatting.
IEEE Transactions on Visualization and Computer Graphics
10.1109/tvcg.2026.3717152
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Abstract
Editing dynamic scenes with 4D Gaussian Splatting (4DGS) is often hampered by spatiotemporal inconsistencies, or “Gaussian drifting”, which degrades edit quality and temporal coherence. We identify that these artifacts stem from two distinct sources: foundational inaccuracies in the initial scene reconstruction, and the disruption of learned trajectories during the editing process itself. To address this, we propose a comprehensive framework that systematically tackles both sources of inconsistency. To solve reconstruction-induced errors, we introduce a novel prior-guided, multi-stage reconstruction pipeline that fuses geometric and motion priors to build a physically plausible and temporally stable foundation. To solve editing-induced errors, we further apply a universal trajectory-preserving technique, which safeguards high-quality motion by decoupling the appearance optimization from the learned deformation. Experiments demonstrate that by systematically addressing both the reconstruction and editing phases, our method achieves state-of-the-art, temporally consistent editing on a wide range of dynamic scenes where previous monolithic approaches fail.
| Item Type: | Article |
|---|---|
| Date Type: | Published Online |
| Status: | In Press |
| Schools: | Schools > Computational & Mathematical Sciences Schools > Computer Science & Informatics |
| Additional Information: | RRS policy applied |
| Publisher: | Institute of Electrical and Electronics Engineers |
| ISSN: | 1077-2626 |
| Date of First Compliant Deposit: | 12 August 2026 |
| Last Modified: | 12 Aug 2026 13:45 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/188702 |
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