Researchers have made a breakthrough in point cloud compression, a crucial step for efficient storage and transmission of 3D data. The new method, called Efficient 3D Point Cloud Compression with Bits-Back Deep Coding, combines deep learning-based spatial and attribute compression with bits-back coding. This approach has been shown to outperform existing state-of-the-art techniques in terms of compression efficiency while maintaining high-quality reconstructions.

The proposed framework uses a neural network to learn a compact latent representation of 3D point coordinates and further compresses this data using bits-back coding. The same technique is applied to compress additional attributes like color associated with each point. This innovative approach takes advantage of statistical patterns in the data, resulting in higher compression ratios than previous methods.

Source: https://dev.to/mikeyoung44/efficient-3d-point-cloud-compression-with-bits-back-deep-coding-2b0n