Providing methods to support semantic interaction with growing volumes of video data is an increasingly important challenge for data mining. To this end, there has been some succes...
This paper proposes a generic method for action recognition
in uncontrolled videos. The idea is to use images
collected from the Web to learn representations of actions
and use ...
Nazli Ikizler-Cinbis, R. Gokberk Cinbis, Stan Scla...
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...
In this paper we present a novel approach using a 4D (x,y,z,t) action feature model (4D-AFM) for recognizing actions from arbitrary views. The 4D-AFM elegantly encodes shape and m...
In this paper, we present a Deformable Action Template
(DAT) model that is learnable from cluttered real-world
videos with weak supervisions. In our generative model,
an action ...