{"ID":2824438,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.23786","arxiv_id":"2512.23786","title":"Bridging the Ex-Vivo to In-Vivo Gap: Synthetic Priors for Monocular Depth Estimation in Specular Surgical Environments","abstract":"Accurate Monocular Depth Estimation (MDE) is critical for autonomous robotic surgery. However, existing self-supervised methods often exhibit a severe \"ex-vivo to in-vivo gap\": they achieve high accuracy on public datasets but struggle in actual clinical deployments. This disparity arises because the severe specular reflections and fluid-filled deformations inherent to real surgeries. Models trained on noisy real-world pseudo-labels consequently suffer from severe boundary collapse. To address this, we leverage the high-fidelity synthetic priors of the \\textit{Depth Anything V2} architecture, which inherently capture precise geometric details, and efficiently adapt them to the medical domain using Dynamic Vector Low-Rank Adaptation (DV-LORA). Our contributions are two-fold. Technically, our approach establishes a new state-of-the-art on the public SCARED dataset; under a novel physically-stratified evaluation protocol, it reduces Squared Relative Error by over 17\\% in high-specularity regimes compared to strong baselines. Furthermore, to provide a rigorous reality check for the field, we introduce \\textbf{ROCAL-T 90} (Real Operative CT-Aligned Laparoscopic Trajectories 90), the first real-surgery validation dataset featuring 90 clinical endoscopic sequences with sub-millimeter ($\u003c 1$mm) ground-truth trajectories. Evaluations on ROCAL-T 90 demonstrate our model's superior robustness in true clinical settings.","short_abstract":"Accurate Monocular Depth Estimation (MDE) is critical for autonomous robotic surgery. However, existing self-supervised methods often exhibit a severe \"ex-vivo to in-vivo gap\": they achieve high accuracy on public datasets but struggle in actual clinical deployments. This disparity arises because the severe specular re...","url_abs":"https://arxiv.org/abs/2512.23786","url_pdf":"https://arxiv.org/pdf/2512.23786v2","authors":"[\"Ankan Aich\",\"Emma D. Ryan\",\"Kris Moe\",\"Isaac Schmale\",\"Li-Xing Man\",\"Yangming Lee\"]","published":"2025-12-29T17:29:42Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.RO\"]","methods":"[\"LoRA\"]","has_code":false}