10 citations · 17 across the 7 of their papers we have counts for
7 papers · 1 filter
Point Tracking in Surgery--The 2025 Surgical Tattoos in Infrared Challenge (STIRC2025)
Adam Schmidt, Mert Asim Karaoglu, Zijian Wu +32
Point tracking in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-based scanning…
LiteTracker: Leveraging Temporal Causality for Accurate Low-latency Tissue Tracking
Mert Asim Karaoglu, Wenbo Ji, Ahmed Abbas +3
Tissue tracking plays a critical role in various surgical navigation and extended reality (XR) applications. While current methods trained on large synthetic datasets achieve high…
Point Tracking in Surgery--The 2024 Surgical Tattoos in Infrared (STIR) Challenge
Adam Schmidt, Mert Asim Karaoglu, Soham Sinha +37
Understanding tissue motion in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-b…
SurgRIPE challenge: Benchmark of Surgical Robot Instrument Pose Estimation
Haozheng Xu, Alistair Weld, Chi Xu +16
Accurate instrument pose estimation is a crucial step towards the future of robotic surgery, enabling applications such as autonomous surgical task execution. Vision-based methods…
FLex: Joint Pose and Dynamic Radiance Fields Optimization for Stereo Endoscopic Videos
Florian Philipp Stilz, Mert Asim Karaoglu, Felix Tristram +3
Reconstruction of endoscopic scenes is an important asset for various medical applications, from post-surgery analysis to educational training. Neural rendering has recently shown…
RIDE: Self-Supervised Learning of Rotation-Equivariant Keypoint Detection and Invariant Description for Endoscopy
Mert Asim Karaoglu, Viktoria Markova, Nassir Navab +2
Unlike in natural images, in endoscopy there is no clear notion of an up-right camera orientation. Endoscopic videos therefore often contain large rotational motions, which require…
DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance Fields
Nicolas Schischka, Hannah Schieber, Mert Asim Karaoglu +6
The accurate reconstruction of dynamic scenes with neural radiance fields is significantly dependent on the estimation of camera poses. Widely used structure-from-motion pipelines…