11 citations · 28 across the 7 of their papers we have counts for
7 papers
CRAYM: Neural Field Optimization via Camera RAY Matching
Liqiang Lin, Wenpeng Wu, Chi-Wing Fu +2
We introduce camera ray matching (CRAYM) into the joint optimization of camera poses and neural fields from multi-view images. The optimized field, referred to as a feature volume,…
Learning Reconstructability for Drone Aerial Path Planning
Yilin Liu, Liqiang Lin, Yue Hu +4
We introduce the first learning-based reconstructability predictor to improve view and path planning for large-scale 3D urban scene acquisition using unmanned drones. In contrast t…
ShapeFormer: Transformer-based Shape Completion via Sparse Representation
Xingguang Yan, Liqiang Lin, Niloy J. Mitra +3
We present ShapeFormer, a transformer-based network that produces a distribution of object completions, conditioned on incomplete, and possibly noisy, point clouds. The resultant d…
Capturing, Reconstructing, and Simulating: the UrbanScene3D Dataset
Liqiang Lin, Yilin Liu, Yue Hu +3
We present UrbanScene3D, a large-scale data platform for research of urban scene perception and reconstruction. UrbanScene3D contains over 128k high-resolution images covering 16 s…
Hausdorff Point Convolution with Geometric Priors
Pengdi Huang, Liqiang Lin, Fuyou Xue +3
Without a shape-aware response, it is hard to characterize the 3D geometry of a point cloud efficiently with a compact set of kernels. In this paper, we advocate the use of Hausdor…
Autonomous Outdoor Scanning via Online Topological and Geometric Path Optimization
Pengdi Huang, Liqiang Lin, Kai Xu +1
Autonomous 3D acquisition of outdoor environments poses special challenges. Different from indoor scenes, where the room space is delineated by clear boundaries and separations (e.…
On Learning the Right Attention Point for Feature Enhancement
Liqiang Lin, Pengdi Huang, Chi-Wing Fu +3
We present a novel attention-based mechanism to learn enhanced point features for point cloud processing tasks, e.g., classification and segmentation. Unlike prior works, which wer…