34 citations · 63 across the 10 of their papers we have counts for
13 papers
3D Meta-Registration: Learning to Learn Registration of 3D Point Clouds
Lingjing Wang, Yu Hao, Xiang Li +1
Deep learning-based point cloud registration models are often generalized from extensive training over a large volume of data to learn the ability to predict the desired geometric…
3D Meta Point Signature: Learning to Learn 3D Point Signature for 3D Dense Shape Correspondence
Hao Huang, Lingjing Wang, Xiang Li +1
Point signature, a representation describing the structural neighborhood of a point in 3D shapes, can be applied to establish correspondences between points in 3D shapes. Conventio…
Unsupervised Partial Point Set Registration via Joint Shape Completion and Registration
Xiang Li, Lingjing Wang, Yi Fang
We propose a self-supervised method for partial point set registration. While recent proposed learning-based methods have achieved impressive registration performance on the full s…
Robust Image Matching By Dynamic Feature Selection
Hao Huang, Jianchun Chen, Xiang Li +2
Estimating dense correspondences between images is a long-standing image under-standing task. Recent works introduce convolutional neural networks (CNNs) to extract high-level feat…
GP-Aligner: Unsupervised Non-rigid Groupwise Point Set Registration Based On Optimized Group Latent Descriptor
Lingjing Wang, Xiang Li, Yi Fang
In this paper, we propose a novel method named GP-Aligner to deal with the problem of non-rigid groupwise point set registration. Compared to previous non-learning approaches, our…
3DMotion-Net: Learning Continuous Flow Function for 3D Motion Prediction
Shuaihang Yuan, Xiang Li, Anthony Tzes +1
In this paper, we deal with the problem to predict the future 3D motions of 3D object scans from previous two consecutive frames. Previous methods mostly focus on sparse motion pre…