1 code implementation • 13 Jan 2025 • Yaqing Ding, Viktor Kocur, Zuzana Berger Haladová, Qianliang Wu, Shen Cai, Jian Yang, Zuzana Kukelova
In this paper, we propose a novel approach for recovering focal lengths from three-view homographies.
1 code implementation • 29 Mar 2024 • Qianliang Wu, Haobo Jiang, Lei Luo, Jun Li, Yaqing Ding, Jin Xie, Jian Yang
Establishing reliable correspondences is essential for registration tasks such as 3D and 2D3D registration.
no code implementations • 31 Dec 2023 • Qianliang Wu, Haobo Jiang, Yaqing Ding, Lei Luo, Jin Xie, Jian Yang
They typically compute candidate correspondences based on distances in the point feature space.
no code implementations • 12 Sep 2023 • Qianliang Wu, Yaqing Ding, Lei Luo, Haobo Jiang, Shuo Gu, Chuanwei Zhou, Jin Xie, Jian Yang
These high-order features are then propagated to dense points and utilized by a Sinkhorn matching module to identify key correspondences for successful registration.
no code implementations • 12 Feb 2023 • Qianliang Wu, Yaqi Shen, Haobo Jiang, Guofeng Mei, Yaqing Ding, Lei Luo, Jin Xie, Jian Yang
Point Cloud Registration is a fundamental and challenging problem in 3D computer vision.
no code implementations • 24 Sep 2020 • Qianliang Wu, Tong Zhang, Zhen Cui, Jian Yang
In this paper, we aim to mine the cue of user preferences in resource-limited recommendation tasks, for which purpose we specifically build a large used car transaction dataset possessing resource-limitation characteristics.