Bedside caregivers assess infants' pain at constant intervals by observing specific
behavioral and physiological signs of pain. This standard has two main limitations. The first …

Denoising diffusion probabilistic models have transformed image generation with their
impressive fidelity and diversity. We show that they also excel in estimating optical flow and …

Deep learning approaches to optical flow estimation have seen rapid progress over the
recent years. One common trait of many networks is that they refine an initial flow estimate …

Motion analysis is one of the most fundamental and challenging problems in the field of
computer vision, which can be widely applied in many areas, such as autonomous driving …

It has been recently shown that a convolutional neural network can learn optical flow
estimation with unsuper-vised learning. However, the performance of the unsuper-vised …

Human activity recognition (HAR) is a complex and multifaceted problem. The research
community has reported numerous approaches to perform HAR. Along with HAR …

Optical flow estimation is one of the oldest and still most active research domains in
computer vision. In 35 years, many methodological concepts have been introduced and …

Optical flow estimation is a crucial task in computer vision that provides low-level motion
information. Despite recent advances, real-world applications still present significant …

This paper provides a comprehensive survey for activity recognition in video surveillance. It
starts with a description of simple and complex human activity, and various applications. The …

Dense motion estimations obtained from optical flow techniques play a significant role in
many image processing and computer vision tasks. Remarkable progress has been made in …