4 accepted papers
Stereo depth estimation has drawn widespread attention from the robotics and vision community due to its broad applications such as 3D reconstruction. Recently, stereo matching foundation models have made significant progress by being trained on the large-scale datasets containing natural images. Ho…
Monocular depth estimation serves as a core technique in endoscopic applications such as 3D reconstruction and localization. However, most existing methods focus primarily on in-domain depth estimation, which limits their robustness and prevents them from delivering impressive cross-domain performan
In computer-assisted orthopedic surgery (CAOS), accurately registering sparse and partial intraoperative point sets with a complete preoperative model remains highly challenging due to limited overlap, extreme sparsity, and point localisation noise. In this paper, we propose a novel end-to-end compl…
In computer-assisted orthopedic surgery (CAOS), accurate point set registration is essential for enhancing surgical accuracy. However, the sparse and low-overlap nature of intraoperative point sets presents significant challenges for reliable registration. To deal with these challenges, we propose a