Anomaly detection, aka outlier detection or novelty detection, has been a lasting yet active
research area in various research communities for several decades. There are still some …

Object detection and tracking is one of the most important and challenging branches in
computer vision, and have been widely applied in various fields, such as health-care …

Conventional wisdom holds that autoregressive models for image generation are typically
accompanied by vector-quantized tokens. We observe that while a discrete-valued space …

Quantizing images into discrete representations has been a fundamental problem in unified
generative modeling. Predominant approaches learn the discrete representation either in a …

As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

An Introduction to Variational Autoencoders Page 1 An Introduction to Variational Autoencoders
Page 2 Other titles in Foundations and Trends R in Machine Learning Computational Optimal …

In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

Learning useful representations without supervision remains a key challenge in machine
learning. In this paper, we propose a simple yet powerful generative model that learns such …

Video surveillance systems are popular and used in public places such as market places,
shop** malls, hospitals, banks, streets, education institutions, city administrative offices …

We propose a novel unpaired image-to-image translation method that uses denoising
diffusion probabilistic models without requiring adversarial training. Our method, UNpaired …