118 citations · 259 across the 10 of their papers we have counts for
11 papers
SCARED-C: Corrected Camera Poses for Endoscopic Depth Estimation
John J. Han, Adam Schmidt, Max Allan +2
The SCARED dataset is a widely used benchmark for endoscopic depth estimation, offering ground-truth 3D reconstructions captured with a structured light sensor. However, the depth…
Online 3D reconstruction and dense tracking in endoscopic videos
Michel Hayoz, Christopher Hahne, Thomas Kurmann +5
3D scene reconstruction from stereo endoscopic video data is crucial for advancing surgical interventions. In this work, we present an online framework for online, dense 3D scene r…
Learning How To Robustly Estimate Camera Pose in Endoscopic Videos
Michel Hayoz, Christopher Hahne, Mathias Gallardo +4
Purpose: Surgical scene understanding plays a critical role in the technology stack of tomorrow's intervention-assisting systems in endoscopic surgeries. For this, tracking the end…
Learning Invariant Representation of Tasks for Robust Surgical State Estimation
Yidan Qin, Max Allan, Yisong Yue +2
Surgical state estimators in robot-assisted surgery (RAS) - especially those trained via learning techniques - rely heavily on datasets that capture surgeon actions in laboratory o…
Stereo Correspondence and Reconstruction of Endoscopic Data Challenge
Max Allan, Jonathan Mcleod, Congcong Wang +21
The stereo correspondence and reconstruction of endoscopic data sub-challenge was organized during the Endovis challenge at MICCAI 2019 in Shenzhen, China. The task was to perform…
daVinciNet: Joint Prediction of Motion and Surgical State in Robot-Assisted Surgery
Yidan Qin, Seyedshams Feyzabadi, Max Allan +2
This paper presents a technique to concurrently and jointly predict the future trajectories of surgical instruments and the future state(s) of surgical subtasks in robot-assisted s…