Video action recognition is widely applied in video indexing, intelligent surveillance,
multimedia understanding, and other fields. Recently, it was greatly improved by …

Understanding human actions in visual data is tied to advances in complementary research
areas including object recognition, human dynamics, domain adaptation and semantic …

Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …

For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

We propose a new self-supervised CNN pre-training technique based on a novel auxiliary
task called odd-one-out learning. In this task, the machine is asked to identify the unrelated …

We introduce the concept of dynamic image, a novel compact representation of videos
useful for video analysis especially when convolutional neural networks (CNNs) are used …

Human motion recognition is one of the most important branches of human-centered
research activities. In recent years, motion recognition based on RGB-D data has attracted …

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

We propose a function-based temporal pooling method that captures the latent structure of
the video sequence data-eg, how frame-level features evolve over time in a video. We show …

We introduce the concept of dynamic image, a novel compact representation of videos
useful for video analysis, particularly in combination with convolutional neural networks …