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EndoGaussian: Real-time Gaussian Splatting for Dynamic Endoscopic Scene Reconstruction

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arxiv 2401.12561 v2 pith:N4E4EVCV submitted 2024-01-23 cs.CV

Yifan Liu , Chenxin Li , Chen Yang , Yixuan Yuan This is my paper
classification cs.CV
keywords gaussianrenderingendoscopicreal-timedeformationendogaussianinitializationscene
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abstract

Reconstructing deformable tissues from endoscopic videos is essential in many downstream surgical applications. However, existing methods suffer from slow rendering speed, greatly limiting their practical use. In this paper, we introduce EndoGaussian, a real-time endoscopic scene reconstruction framework built on 3D Gaussian Splatting (3DGS). By integrating the efficient Gaussian representation and highly-optimized rendering engine, our framework significantly boosts the rendering speed to a real-time level. To adapt 3DGS for endoscopic scenes, we propose two strategies, Holistic Gaussian Initialization (HGI) and Spatio-temporal Gaussian Tracking (SGT), to handle the non-trivial Gaussian initialization and tissue deformation problems, respectively. In HGI, we leverage recent depth estimation models to predict depth maps of input binocular/monocular image sequences, based on which pixels are re-projected and combined for holistic initialization. In SPT, we propose to model surface dynamics using a deformation field, which is composed of an efficient encoding voxel and a lightweight deformation decoder, allowing for Gaussian tracking with minor training and rendering burden. Experiments on public datasets demonstrate our efficacy against prior SOTAs in many aspects, including better rendering speed (195 FPS real-time, 100$\times$ gain), better rendering quality (37.848 PSNR), and less training overhead (within 2 min/scene), showing significant promise for intraoperative surgery applications. Code is available at: \url{https://yifliu3.github.io/EndoGaussian/}.

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Cited by 7 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Gastroendoscopy View Synthesis: A New Real Dataset and Evaluation

    cs.CV 2026-06 unverdicted novelty 7.0 of 10

    Presents the GastroNVS dataset of real gastroscopic images with poses and point cloud, evaluates 3DGS methods on it, and discusses challenges.

  2. EndoVGGT: GNN-Enhanced Depth Estimation for Surgical 3D Reconstruction

    cs.CV 2026-03 unverdicted novelty 7.0 of 10

    EndoVGGT uses a dynamic DeGAT graph attention module to improve depth estimation and non-rigid 3D reconstruction in surgery, reporting 24.6% PSNR and 9.1% SSIM gains on SCARED with zero-shot generalization to new domains.

  3. DeGenseGS: Geometrically and Semantically Decoupled Surgical Scene Understanding in 4D Gaussian Splatting

    cs.CV 2026-07 conditional novelty 5.5 of 10

    Decoupling geometry and semantics in 4DGS via HexPlane kinematic latents and rasterization-native extraction raises surgical semantic mIoU from 53.46% to 68.20% on CholecSeg8k.

  4. G-SHARP: Gaussian Surgical Hardware Accelerated Real-time Pipeline

    cs.CV 2025-12 unverdicted novelty 5.0 of 10

    G-SHARP is a Gaussian splatting pipeline for real-time deformable tissue reconstruction in surgery, built on the open GSplat rasterizer and deployed via Holoscan on NVIDIA edge hardware with claimed state-of-the-art r...

  5. ROOM: A Physics-Based Continuum Robot Simulator for Photorealistic Medical Datasets Generation

    cs.RO 2025-09 conditional novelty 5.0 of 10

    ROOM is an open simulation pipeline that generates photorealistic, multimodal synthetic bronchoscopy data from CT scans, and fine-tuning depth models on this data improves their performance on an external phantom-base...

  6. ColorGS: High-fidelity Surgical Scene Reconstruction with Colored Gaussian Splatting

    cs.CV 2025-08 conditional novelty 3.0 of 10

    ColorGS adds spatially anchored colors and a time-independent deformation offset to 3D Gaussian Splatting, achieving 39.85 PSNR on EndoNeRF, 1.5 dB above Deform3DGS.

  7. A Survey on 3D Gaussian Splatting

    cs.CV 2024-01 unverdicted novelty 2.0 of 10

    A survey compiling principles, applications, benchmarks, and challenges of 3D Gaussian Splatting for explicit 3D scene representation.

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