In this competitive world, the supervision and monitoring of human resources are primary
and necessary tasks to drive context-aware applications. Advancement in sensor and …

Computer vision has a great potential to help our daily lives by searching for lost keys,
watering flowers or reminding us to take a pill. To succeed with such tasks, computer vision …

This paper surveys the state of the art on multimodal gesture recognition and introduces the
JMLR special topic on gesture recognition 2011–2015. We began right at the start of the …

In a given scene, humans can easily predict a set of immediate future events that might
happen. However, pixel-level anticipation in computer vision is difficult because machine …

Abstract Temporal Action Localization (TAL) in untrimmed video is important for many
applications. But it is very expensive to annotate the segment-level ground truth (action class …

Object proposals have contributed significantly to recent advances in object understanding
in images. Inspired by the success of this approach, we introduce Deep Action Proposals …

Analyzing videos of human actions involves understanding the temporal relationships
among video frames. State-of-the-art action recognition approaches rely on traditional …

We propose a weakly-supervised framework for action labeling in video, where only the
order of occurring actions is required during training time. The key challenge is that the per …

In online action detection, the goal is to detect the start of an action in a video stream as
soon as it happens. For instance, if a child is chasing a ball, an autonomous car should …

In this paper, we propose a new Dividing and Aggregating Network (DA-Net) for multi-view
action recognition. In our DA-Net, we learn view-independent representations shared by all …