A list of papers and datasets about point cloud analysis (processing)
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Updated
May 19, 2023
A list of papers and datasets about point cloud analysis (processing)
C++ library and programs for reading and writing ASPRS LAS format with LiDAR data
Image Signal Processing (ISP) Guide. Learn all about the process of converting an image/video into digital form by performing tasks like noise reduction, filtering, auto exposure, autofocus, HDR correction, and image sharpening with a Specialized type of media processor.
Morphing and Sampling Network for Dense Point Cloud Completion (AAAI2020)
Implementations of a rather simple version of the Iterative Closest Point algorithm in various languages.
Papers, code and datasets about deep learning for 3D Object Detection.
Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions (RAL 2022)
[ICCV 2021] Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis
Repo for "Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions" https://arxiv.org/abs/2201.12296
Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"
Probabilistic line extraction from 2-D range scan
An SDK for multi-agent collaborative perception.
[NeurIPS2021] Learning Distilled Collaboration Graph for Multi-Agent Perception
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…
PVT: Point-Voxel Transformer for 3D Deep Learning
Introduction to Point Cloud Processing
Cross-platform library to communicate with LiDAR devices of the Blickfeld GmbH.
[CVPR2023] Deep Graph-based Spatial Consistency for Robust Non-rigid Point Cloud Registration
In this project we detect, segment and track the obstacles of an ego car and its custom implementation of KDTree, obstacle detection, segmentation, clustering and tracking algorithm in C++ and compare it to the inbuilt algorithm functions of PCL library on a LiDAR's point cloud data.
Official GitHub repo for VecKM. A very efficient and descriptive local geometry encoder / point tokenizer / patch embedder. ICML2024.
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