Open3D: A Modern Library for 3D Data Processing
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Summary
Open3D is an open-source library that supports rapid development of software that deals with 3D data and is used in a number of published research projects and is actively deployed in the cloud.
- Type
- preprint
- Published
- 2018-01-30
- Cited by
- 2,217
- References
- 24
- Access
- Open access
- OpenAlex
- https://openalex.org/W2786036844
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:34198369
Keywords
Computer science, Data science, Information retrieval
References
- Point primitives for interactive modeling and processing of 3D-geometry
- MeshLab: an Open-Source Mesh Processing Tool
- Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology
- Object modeling by registration of multiple range images
- Robust reconstruction of indoor scenes
- SUN3D: A Database of Big Spaces Reconstructed Using SfM and Object Labels
- A volumetric method for building complex models from range images
- A benchmark for the evaluation of RGB-D SLAM systems
- A Method for Registration of 3-D Shapes
- Scalable Nearest Neighbor Algorithms for High Dimensional Data
- 3D is here: Point Cloud Library (PCL)
- Fast Point Feature Histograms (FPFH) for 3D registration
- SceneNN: A Scene Meshes Dataset with aNNotations
- Learning Compact Geometric Features
- Colored Point Cloud Registration Revisited
- Object modelling by registration of multiple range images
- The OpenCV library
- Indoor Segmentation and Support Inference from RGBD Images
- Fast Global Registration
- TensorFlow: A system for large-scale machine learning
Cited by
- TAToo: vision-based joint tracking of anatomy and tool for skull-base surgery
- Tangent Convolutions for Dense Prediction in 3D
- cilantro: A Lean, Versatile, and Efficient Library for Point Cloud Data Processing
- Learning to Predict 3D Surfaces of Sculptures from Single and Multiple Views
- Adversarial point set registration
- DeepMapping: Unsupervised Map Estimation From Multiple Point Clouds
- Improved Iterative Closest Point Algorithm using Truncated Signed Distance Function
- Taking a Deeper Look at the Inverse Compositional Algorithm
- Extreme Relative Pose Estimation for RGB-D Scans via Scene Completion
- An Implementation of Reinforcement Learning in Assembly Path Planning based on 3D Point Clouds
- High-Accuracy Globally Consistent Surface Reconstruction Using Fringe Projection Profilometry
- Automotive 3D Object Detection Without Target Domain Annotations
- Pyoints: A Python package for point cloud, voxel and raster processing
- ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging
- Deciphering interaction fingerprints from protein molecular surfaces
- Casting Geometric Constraints in Semantic Segmentation as Semi-Supervised Learning
- Three-dimensional Underwater Environment Reconstruction with Graph Optimization Using Acoustic Camera
- Deep Closest Point: Learning Representations for Point Cloud Registration
- What Do Single-View 3D Reconstruction Networks Learn?
- Where Am I: Localization and 3D Maps for Autonomous Vehicles
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