A discriminative CNN video representation for event detection
In this paper, we propose a discriminative video representation for event detection over a
large scale video dataset when only limited hardware resources are available. The focus of …
large scale video dataset when only limited hardware resources are available. The focus of …
Exploiting feature and class relationships in video categorization with regularized deep neural networks
In this paper, we study the challenging problem of categorizing videos according to high-
level semantics such as the existence of a particular human action or a complex event …
level semantics such as the existence of a particular human action or a complex event …
Semantic pooling for complex event analysis in untrimmed videos
Pooling plays an important role in generating a discriminative video representation. In this
paper, we propose a new semantic pooling approach for challenging event analysis tasks …
paper, we propose a new semantic pooling approach for challenging event analysis tasks …
Exploring inter-feature and inter-class relationships with deep neural networks for video classification
Videos contain very rich semantics and are intrinsically multimodal. In this paper, we study
the challenging task of classifying videos according to their high-level semantics such as …
the challenging task of classifying videos according to their high-level semantics such as …
Videostory: A new multimedia embedding for few-example recognition and translation of events
This paper proposes a new video representation for few-example event recognition and
translation. Different from existing representations, which rely on either low-level features, or …
translation. Different from existing representations, which rely on either low-level features, or …
Super fast event recognition in internet videos
Techniques for recognizing high-level events in consumer videos on the Internet have many
applications. Systems that produced state-of-the-art recognition performance usually contain …
applications. Systems that produced state-of-the-art recognition performance usually contain …
Arch: Adaptive recurrent-convolutional hybrid networks for long-term action recognition
M Xin, H Zhang, H Wang, M Sun, D Yuan - Neurocomputing, 2016 - Elsevier
Recognition of human actions from digital video is a challenging task due to complex
interfering factors in uncontrolled realistic environments. In this paper, we propose a …
interfering factors in uncontrolled realistic environments. In this paper, we propose a …
Personalized video recommendation using rich contents from videos
Video recommendation has become an essential way of helping people explore the
massive videos and discover the ones that may be of interest to them. In the existing video …
massive videos and discover the ones that may be of interest to them. In the existing video …
Hierarchical concept score postprocessing and concept-wise normalization in CNN-based video event recognition
M Soltanian, S Ghaemmaghami - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper is focused on video event recognition based on frame level convolutional neural
network (CNN) descriptors. Using transfer learning, the image trained descriptors are …
network (CNN) descriptors. Using transfer learning, the image trained descriptors are …
Video event detection using generalized subclass discriminant analysis and linear support vector machines
N Gkalelis, V Mezaris - Proceedings of international conference on …, 2014 - dl.acm.org
In this paper, a two-phase approach to event detection in video is proposed. This combines
a novel nonlinear Discriminant Analysis (DA) method called Generalized Subclass DA …
a novel nonlinear Discriminant Analysis (DA) method called Generalized Subclass DA …