Endo-TSR: 内視鏡再構成のための時空間スペクトルモデリング
Endo-TSR: Temporal Spectral Modeling of Appearance and Motion for Endoscopic Reconstruction
内視鏡シーン再構成において、変形ガウスモデルにフーリエ色残差と並進残差を導入し、組織の動きと外観変化を時空間的にモデル化する手法を提案。EndoNeRFとStereoMISで最高PSNRを達成。
著者: Taoyu Wu, Yiyi Miao, Qi Shao, Zhuoxiao Li, Zhe Tang, Limin Yu, Baoru Huang
分類: cs.CV, cs.RO
原文アブストラクト
Endoscopic scene reconstruction requires modeling tissue motion and temporal appearance while recovering fine surface detail. Deformable Gaussian models provide explicit trajectories, but their fixed colour coefficients lack a dedicated temporal representation for photometric changes. We propose Endo-TSR, which augments deformable Gaussian splatting with bounded Fourier colour residuals and independent translation residuals on shared temporal frequencies. The colour residuals capture local appearance changes, while a Matérn spectral prior regularises motion corrections. Multi-scale Laplacian supervision guides tissue-detail recovery during joint image fitting. Extensive experiments on the EndoNeRF and StereoMIS datasets demonstrate state-of-the-art rendering quality, with the highest PSNR across all evaluated sequences. Ablation studies show that temporal appearance yields the largest PSNR gain among the tested component additions, while appearance and detail supervision jointly improve rendering with fixed Gaussian counts.