Efficient rendering of photo‐realistic virtual worlds is a long standing effort of computer
graphics. Modern graphics techniques have succeeded in synthesizing photo‐realistic …

Pedestrian detection and tracking have become an important field in the computer vision
research area. This growing interest, started in the last decades, might be explained by the …

A neural radiance field (NeRF) is a scene model supporting high-quality view synthesis,
optimized per scene. In this paper, we explore enabling user editing of a category-level …

Abstract We present Neural Articulated Radiance Field (NARF), a novel deformable 3D
representation for articulated objects learned from images. While recent advances in 3D …

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 …

We propose an alternative generator architecture for generative adversarial networks,
borrowing from style transfer literature. The new architecture leads to an automatically …

Deep convolutional networks have become a popular tool for image generation and
restoration. Generally, their excellent performance is imputed to their ability to learn realistic …

Perception and being active (having a certain level of motion freedom) are closely tied.
Learning active perception and sensorimotor control in the physical world is cumbersome as …

While humans easily recognize relations between data from different domains without any
supervision, learning to automatically discover them is in general very challenging and …

Recent advances in deep learning, especially deep convolutional neural networks (CNNs),
have led to significant improvement over previous semantic segmentation systems. Here we …