2024
Reducing the Complexity of Normalizing Flow Architectures for Point Cloud Attribute Compression
ICASSP 2024accepted
Existing learning-based methods to compress PCs attributes typically employ variational autoencoders (VAE) to learn compact signal representations. However, these schemes suffer from limited reconstruction quality at high bitrates due to their intrinsic lossy nature. More recently, normalizing flows…