Over the last decade, the availability of public image repositories and recognition
benchmarks has enabled rapid progress in visual object category and instance detection …

We introduce a new large-scale video dataset designed to assess the performance of
diverse visual event recognition algorithms with a focus on continuous visual event …

We present an extensive three year study on economically annotating video with
crowdsourced marketplaces. Our public framework has annotated thousands of real world …

This paper presents a new benchmark dataset for validating vision-based methods that
automatically identifies visually distinctive working activities of excavators and dump trucks …

Given the enormous growth in user-generated videos, it is becoming increasingly important
to be able to navigate them efficiently. As these videos are generally of poor quality …

Tracking and identifying players in sports videos filmed with a single pan-tilt-zoom camera
has many applications, but it is also a challenging problem. This paper introduces a system …

Understanding human behaviors is a challenging problem in computer vision that has
recently seen important advances. Human behavior understanding combines image and …

Automated driving will have a big impact on society, creating new possibilities for mobility
and reducing road accidents. Current developments aim to provide driver assistance in the …

Our goal is to segment a video sequence into moving objects and the world scene. In recent
work, spectral embedding of point trajectories based on 2D motion cues accumulated from …

Millions of learners today use how-to videos to master new skills in a variety of domains. But
browsing such videos is often tedious and inefficient because video player interfaces are not …