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Efficient Hierarchical Entropy Model for Learned Point Cloud Compression
Computer Vision and Pattern Recognition, 2023Learning an accurate entropy model is a fundamental way to remove the redundancy in point cloud compression. Recently, the octree-based auto-regressive entropy model which adopts the self-attention mechanism to explore dependencies in a large-scale ...
Rui Song, Chunyang Fu, Shan Liu, Ge Li
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Real-time point cloud compression
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015With today's advanced 3D scanner technology, huge amounts of point cloud data can be generated in short amounts of time. Data compression is thus necessary for storage and especially for transmission, e.g., via wireless networks. While previous approaches delivered good compression ratios and interesting theoretical insights, they are either ...
Tim Golla, Reinhard Klein
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Rate Control for Geometry-Based LiDAR Point Cloud Compression via Multi-Factor Modeling
IEEE transactions on broadcastingGeometry-based Point Cloud Compression (G-PCC) standard developed by the Moving Picture Experts Group has shown a promising prospect for compressing extremely sparse point clouds captured by the Light Detection And Ranging (LiDAR) equipment.
Lizhi Hou +5 more
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Rate-distortion optimized quantization for geometry-based point cloud compression
J. Electronic Imaging, 2023. Limited by the network bandwidth, three-dimensional (3D) point cloud needs to be efficiently compressed before transmission. As one of the three attribute coding methods adopted in the geometry-based point cloud compression (G-PCC) standard developed ...
Tianzhao Guo +3 more
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H-PCC: Point Cloud Compression With Hybrid Mode Selection and Content Adaptive Down-Sampling
IEEE Robotics and Automation LettersLiDAR sensors are integral to autonomous driving and augmented reality applications, providing essential depth information. However, managing the substantial volume of LiDAR point cloud data is crucial for practical application, necessitating efficient ...
Bowen Liu +4 more
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Point Cloud Compression and Objective Quality Assessment: A Survey
arXiv.orgThe rapid growth of 3D point cloud data, driven by applications in autonomous driving, robotics, and immersive environments, has led to criticals demand for efficient compression and quality assessment techniques.
Yiling Xu +8 more
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Compression of Dense and Regular Point Clouds
Computer Graphics Forum, 2006Abstract We present a simple technique for single‐rate compression of point clouds sampled from a surface, based on a spanning tree of the points. Unlike previous methods, we predict future vertices using both a linear predictor, which uses the previous edge as a predictor for the current edge, and lateral predictors that rotate the previous edge 90 ...
Merry, Mr. Bruce +2 more
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Quantitative Comparison of Point Cloud Compression Algorithms With PCC Arena
IEEE transactions on multimedia, 2023With the growth of Extended Reality (XR) and capturing devices, point cloud representation has become attractive to academics and industry. Point Cloud Compression (PCC) algorithms further promote numerous XR applications that may change our daily life ...
Cheng-Hao Wu +5 more
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Denoising Diffusion Probabilistic Model for Point Cloud Compression at Low Bit-Rates
IEEE International Conference on Multimedia and ExpoEfficient compression of low-bit-rate point clouds is critical for bandwidth-constrained applications. However, existing techniques mainly focus on high-fidelity reconstruction, requiring many bits for compression.
Gabriele Spadaro +7 more
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View-Dependent Dynamic Point Cloud Compression
IEEE Transactions on Circuits and Systems for Video Technology, 2021Dynamic point cloud (DPC) captures 3D object and scene with realistic appearance to mimic the natural reality. It inherently offers the six-degree-of-freedom (6DoF) for content consumption, which motivates us to facilitate the network-friendly view-dependent DPC streaming by leveraging the limited field of view of the human visual system (HVS) at ...
Wenjie Zhu +4 more
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