We address recognition and localization of human actions in realistic scenarios. In contrast to the previous work studying human actions in controlled settings, here we train and ...
The aim of this paper is to address recognition of natural human actions in diverse and realistic video settings. This challenging but important subject has mostly been ignored in...
Ivan Laptev, Marcin Marszalek, Cordelia Schmid, Be...
We present a method to classify movies on the basis of audio-visual cues present in the previews. A preview summarizes the main idea of a movie providing suitable amount of inform...
We describe a novel video player that uses Temporal Semantic Compression (TSC) to present a compressed summary of a movie. Compression is based on tempo which is derived from film...
Abstract. Movies and TV are a rich source of diverse and complex video of people, objects, actions and locales "in the wild". Harvesting automatically labeled sequences o...
Timothee Cour, Chris Jordan, Eleni Miltsakaki, Ben...