EndoWave: Rational-Wavelet 4D Gaussian Splatting for Endoscopic Reconstruction
Taoyu Wu, Yiyi Miao, Jiaxin Guo, Ziyan Chen, Sihang Zhao, Zhuoxiao Li, Zhe Tang, Baoru Huang, Limin Yu

TL;DR
EndoWave introduces a novel 4D Gaussian splatting framework with optical flow and wavelet constraints to improve 3D endoscopic reconstruction amidst challenging visual artifacts.
Contribution
The paper presents a unified 4D Gaussian splatting method incorporating optical flow and wavelet supervision for more accurate endoscopic 3D reconstruction.
Findings
Achieves state-of-the-art reconstruction quality on real datasets.
Enhances temporal coherence and scene structure accuracy.
Improves rendering performance with wavelet constraints.
Abstract
In robot-assisted minimally invasive surgery, accurate 3D reconstruction from endoscopic video is vital for downstream tasks and improved outcomes. However, endoscopic scenarios present unique challenges, including photometric inconsistencies, non-rigid tissue motion, and view-dependent highlights. Most 3DGS-based methods that rely solely on appearance constraints for optimizing 3DGS are often insufficient in this context, as these dynamic visual artifacts can mislead the optimization process and lead to inaccurate reconstructions. To address these limitations, we present EndoWave, a unified spatio-temporal Gaussian Splatting framework by incorporating an optical flow-based geometric constraint and a multi-resolution rational wavelet supervision. First, we adopt a unified spatio-temporal Gaussian representation that directly optimizes primitives in a 4D domain. Second, we propose a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
