Results 11 to 20 of about 264,137 (214)
Efficient Large-Scale Point Cloud Geometry Compression
SensorsDue to the significant bandwidth and memory requirements for transmitting and storing large-scale point clouds, considerable progress has been made in recent years in the field of large-scale point cloud geometry compression.
Shiyu Lu, Cheng Han, Huamin Yang
doaj +3 more sources
Saliency-Guided Point Cloud Compression for 3D Live Reconstruction
Multimodal Technologies and Interaction3D modeling and reconstruction are critical to creating immersive XR experiences, providing realistic virtual environments, objects, and interactions that increase user engagement and enable new forms of content manipulation. Today, 3D data can be easily
Pietro Ruiu +2 more
doaj +2 more sources
OctAttention: Octree-based Large-scale Contexts Model for Point Cloud Compression [PDF]
AAAI Conference on Artificial Intelligence, 2022 In point cloud compression, sufficient contexts are significant for modeling the point cloud distribution. However, the contexts gathered by the previous voxel-based methods decrease when handling sparse point clouds.
Chunyang Fu +4 more
semanticscholar +1 more source
3D Point Cloud Compression [PDF]
The 24th International Conference on 3D Web Technology, 2019 In recent years, 3D point clouds have enjoyed a great popularity for representing both static and dynamic 3D objects. When compared to 3D meshes, they offer the advantage of providing a simpler, denser and more close-to-reality representation. However, point clouds always carry a huge amount of data.
Chao Cao, Marius Preda, Titus Zaharia
openaire +2 more sources
VoxelContext-Net: An Octree based Framework for Point Cloud Compression [PDF]
Computer Vision and Pattern Recognition, 2021 In this paper, we propose a two-stage deep learning framework called VoxelContext-Net for both static and dynamic point cloud compression. Taking advantages of both octree based methods and voxel based schemes, our approach employs the voxel context to ...
Z. Que, Guo Lu, Dong Xu
semanticscholar +1 more source
Multiscale Point Cloud Geometry Compression [PDF]
2021 Data Compression Conference (DCC), 2021 Recent years have witnessed the growth of point cloud based applications because of its realistic and fine-grained representation of 3D objects and scenes. However, it is a challenging problem to compress sparse, unstructured, and high-precision 3D points for efficient communication.
Wang, Jianqiang +3 more
openaire +2 more sources
Predictive point-cloud compression [PDF]
ACM SIGGRAPH 2005 Sketches on - SIGGRAPH '05, 2005 Point clouds have recently become a popular alternative to polygonal meshes for representing three-dimensional geometric models. 3D photography and scanning systems acquire the geometry and appearance of real-world objects in form of point samples.
Stefan Gumhold +3 more
openaire +4 more sources
TransPCGC: Point Cloud Geometry Compression Based on Transformers
Algorithms, 2023 Due to the often substantial size of the real-world point cloud data, efficient transmission and storage have become critical concerns. Point cloud compression plays a decisive role in addressing these challenges.
Shiyu Lu, Huamin Yang, Cheng Han
doaj +1 more source
Folding-Based Compression Of Point Cloud Attributes [PDF]
2020 IEEE International Conference on Image Processing (ICIP), 2020 Existing techniques to compress point cloud attributes leverage either geometric or video-based compression tools. We explore a radically different approach inspired by recent advances in point cloud representation learning. Point clouds can be interpreted as 2D manifolds in 3D space.
Quach, Maurice +2 more
openaire +2 more sources
Quality evaluation of point cloud compression techniques
Signal Processing: Image Communication, 2023 J. Prazeres +2 more
semanticscholar +2 more sources