# Egosurg: Arbitrary view synthesis for egocentric replay of operating room workflows from ambient cameras

arXiv: https://arxiv.org/abs/2510.04802 · HTML: https://mlsanity.com/paper/2510.04802/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 20 references that are in the map.
- First posted on arXiv 6 Oct 2025.

## Builds on (most cited first, 11 of 11)

- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [Adversarial Diffusion Distillation](https://mlsanity.com/paper/2311.17042/) (2023)
- [Neuralangelo: High-Fidelity Neural Surface Reconstruction](https://mlsanity.com/paper/2306.03092/) (2023)
- [FoundationStereo: Zero-Shot Stereo Matching](https://mlsanity.com/paper/2501.09898/) (2025)
- [Difix3D+: Improving 3D Reconstructions with Single-Step Diffusion Models](https://mlsanity.com/paper/2503.01774/) (2025)
- [Taming Video Diffusion Prior with Scene-Grounding Guidance for 3D Gaussian Splatting from Sparse Inputs](https://mlsanity.com/paper/2503.05082/) (2025)
- [EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity Understanding](https://mlsanity.com/paper/2505.24287/) (2025)
- [Pelphix: Surgical Phase Recognition from X-ray Images in Percutaneous Pelvic Fixation](https://mlsanity.com/paper/2304.09285/) (2023)
- [StraightTrack: Towards Mixed Reality Navigation System for Percutaneous K-wire Insertion](https://mlsanity.com/paper/2410.01143/) (2024)
- [Seamless Augmented Reality Integration in Arthroscopy: A Pipeline for Articular Reconstruction and Guidance](https://mlsanity.com/paper/2410.00386/) (2024)
- [Privacy-Preserving Operating Room Workflow Analysis using Digital Twins](https://mlsanity.com/paper/2504.12552/) (2025)

## Built on by (most cited first, 1 of 1)

- [TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Research](https://mlsanity.com/paper/2511.07412/) (2025)

## Abstract (arXiv)

Observing surgical practice has historically relied on fixed vantage points or recollections, leaving the egocentric perspectives that shape clinical decisions undocumented. Ambient fixed cameras capture the operating room (OR) at room scale but cannot recover what any individual team member actually saw. We present EgoSurg, a framework that reconstructs dynamic OR scenes from sparse wall-mounted stereo video and renders arbitrary, role-specific egocentric views without instrumenting personnel or interfering with clinical workflow. EgoSurg initializes a per-timestamp 3D Gaussian Splatting representation from scale-aware stereo depth and refines it with an image-conditioned diffusion model that corrects auxiliary rendered views, mitigating artifacts caused by limited camera coverage, crowding, and occlusion. We evaluated the framework on four real robotic pulmonology procedures and two simulated full-workflow sessions across two hospital sites. Near-field reconstruction fidelity was consistent (PSNR 26.8~dB, SSIM .895) across five workflow phases and both sites, and synthesized egocentric views reached a PSNR of 17.8~dB and an SSIM of .766 against paired hand-held point-of-view recordings. We further demonstrate three case studies for intended use: adjudicating a simulated sterile field violation, replaying a procedure from role-specific viewpoints, and testing a counterfactual change in personnel position. These results indicate that existing ambient camera infrastructure can be turned into a navigable 3D record of surgical work, supporting retrospective review of safety events, training, and workflow analysis from every angle.