ABSTRACT: Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera ...

Generative Modeling is a branch of machine learning that focuses on creating models representing distributions of data, denoted as $P(X)$. $X$ represents the data ...

Abstract: Vector quantized variational autoencoders, as variants of variational autoencoders, effectively capture discrete representations by quantizing continuous latent spaces and are widely used in ...

If you’re completely new to Microsoft Word, you’re probably wondering where to begin. You’ve come to the right place because we’ll get you started. From what you see in the Word window to how to save ...

This project provides a comprehensive analysis of Variational Autoencoders (VAE) and traditional Autoencoders (AE) for image compression tasks. The analysis focuses on the impact of various model ...

Abstract: Variational Graph Autoencoders (VAGE) emerged as powerful graph representation learning methods with promising performance on graph analysis tasks. However, existing methods typically rely ...