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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt età la diffusion(More)
— The AXES project participated in the interactive instance search task (INS), the semantic indexing task (SIN), the multimedia event detection task (MED) and the multimedia event recounting task (MER) for TRECVid 2013. Our interactive INS focused this year on using classifiers trained at query time with positive examples collected from external search(More)
— The AXES project participated in the interactive instance search task (INS), the known-item search task (KIS), and the multimedia event detection task (MED) for TRECVid 2012. As in our TRECVid 2011 system, we used nearly identical search systems and user interfaces for both INS and KIS. Our interactive INS and KIS systems focused this year on using(More)
This paper describes our participation to the 2014 edition of the TrecVid Multimedia Event Detection task. Our system is based on a collection of local visual and audio de-scriptors, which are aggregated to global descriptors, one for each type of low-level descriptor, using Fisher vectors. Besides these features, we use two features based on convolutional(More)
Single-molecule detection enables us to visualise the real-time dynamics of individual molecules in live cells. We review the recent advancements in single-molecule fluorescence tracking of receptor protein mobility in the neuronal membrane. First, we discuss the practical consideration of single-molecule tracking in neurones, including the choice of cells(More)
While important advances were recently made towards temporally localizing and recognizing specific human actions or activities in videos, efficient detection and classification of long video chunks belonging to semantically-defined categories such as " pursuit " or " romance " remains challenging. We introduce a new dataset, Action Movie Franchises,(More)
Automatic interpretation and understanding of videos still remains at the frontier of computer vision. The core challenge is to lift the expressive power of the current visual features (as well as features from other modalities, such as audio or text) to be able to automatically recognize typical video sections, with low temporal saliency yet high semantic(More)
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