Nicolas Frank’s scientific contributions

... This residual coding neural network consists of an autoencoder, quantization, and a variational hyperprior for adaptive entropy coding architecture, similar to [29], but the decoder additionally includes a CNN-based refiner module that receives the output of the autoencoder and the distorted PC from the base layer, producing the enhancement layer PC. Frank et al. [34] later proposed a latent space slicing approach to improve the entropy coding in the commonly adopted autoencoder with variational hyperprior architecture. In the proposed approach, the latent representation produced by the autoencoder is sliced along the channel dimension, with each slice being separately entropy coded. ...

Reference:

The JPEG Pleno Learning-based Point Cloud Coding Standard: Serving Man and Machine