Abstract Human Action Recognition (HAR) is a challenging task used in sports such as
volleyball, basketball, soccer, and tennis to detect players and recognize their actions and …

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

摘要随着摄像头安装数量的日益增多, 以及智慧城市和公共安全需求的日益增长,
采用人工的视频监控方式已经远远不能满足需要, 因此智能视频监控技术应运而生并迅速成为 …

Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …

Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …

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 …

On public benchmarks, current action recognition techniques have achieved great success.
However, when used in real-world applications, eg sport analysis, which requires the …

Neural networks trained on datasets such as ImageNet have led to major advances in visual
object classification. One obstacle that prevents networks from reasoning more deeply about …

This paper introduces a video dataset of spatio-temporally localized Atomic Visual Actions
(AVA). The AVA dataset densely annotates 80 atomic visual actions in 437 15-minute video …

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 …