Autoencoder

PCGen: A Fully Parallelizable Point Cloud Generative Model

Generative models have the potential to revolutionize 3D extended reality. A primary obstacle is that augmented and virtual reality need real-time computing. Current state-of-the-art point cloud random generation methods are not fast enough for these …

Efficient local image descriptors learned with autoencoders

Local image descriptors play a crucial role in many image processing tasks, such as object tracking, object recognition, panorama stitching, and image retrieval. In this paper, we focus on learning local image descriptors in an unsupervised way, …

Partial convolution based multimodal autoencoder for art investigation

Autoencoders have been widely used in applications with limited annotations to extract features in an unsupervised manner, pre-processing the data to be used in machine learning models. This is especially helpful in image processing for art …