[ECCV 2022] Official pytorch implementation of the paper, "PointMixer: MLP-Mixer for Point Cloud Understanding"

Point cloud completion tool based on dictionary learning. Takes a PCL point cloud surface and fills in gaps or densifies sparse regions by learning from the various surface features of the cloud. This is done using a variation of the k-SVD dictionary learning algorithm that allows for continuous atoms and dealing with unstructured point cloud da…

High-Fidelity 3D Reconstruction via Graph Optimization. A Multi-Frame Registration and reconstruction algorithm.

Code for Point Cloud Generation

Dynamic geometric methods with convolutional occupancy networks

The official implementation of the paper titled "A High-Performance Learning-Based Framework for Monocular 3D Point Cloud Reconstruction" accepted in the IEEE Journal of Radio Frequency Identification (JRFID) for 2024