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Xingtong Liu

4 accepted papers

2022

SAGE: SLAM with Appearance and Geometry Prior for Endoscopy

ICRA 2022poster

In endoscopy, many applications (e.g., surgical navigation) would benefit from a real-time method that can simultaneously track the endoscope and reconstruct the dense 3D geometry of the observed anatomy from a monocular endoscopic video. To this end, we develop a Simultaneous Localization and Mappi…

Cited by 44SourcecodeScholar
2021

Neighborhood Normalization for Robust Geometric Feature Learning

CVPR 2021poster

Extracting geometric features from 3D models is a common first step in applications such as 3D registration, tracking, and scene flow estimation. Many hand-crafted and learning-based methods aim to produce consistent and distinguishable geometric features for 3D models with partial overlap. These me…

Cited by 6PDFcodeScholar
2021

Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective With Transformers

ICCV 2021poster

Stereo depth estimation relies on optimal correspondence matching between pixels on epipolar lines in the left and right images to infer depth. In this work, we revisit the problem from a sequence-to-sequence correspondence perspective to replace cost volume construction with dense pixel matching us…

Cited by 338PDFcodeScholar
2020

Extremely Dense Point Correspondences Using a Learned Feature Descriptor

CVPR 2020poster

High-quality 3D reconstructions from endoscopy video play an important role in many clinical applications, including surgical navigation where they enable direct video-CT registration. While many methods exist for general multi-view 3D reconstruction, these methods often fail to deliver satisfactory…

Cited by 62PDFcodeScholar