Search Results for author:
Found 4 papers, 2 papers with code
Mini-Splatting: Representing Scenes with a Constrained Number of Gaussians
In this study, we explore the challenge of efficiently representing scenes with a constrained number of Gaussians.
4DAC: Learning Attribute Compression for Dynamic Point Clouds
In addition, we also propose a deep conditional entropy model to estimate the probability distribution of the transformed coefficients, by incorporating temporal context from consecutive point clouds and the motion estimation/compensation modules.
3DAC: Learning Attribute Compression for Point Clouds
Finally, the estimated probabilities are used to further compress these transform coefficients to a final attributes bitstream.
SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds
Labelling point clouds fully is highly time-consuming and costly.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
