17,664 research outputs found
Graph Distillation for Action Detection with Privileged Modalities
We propose a technique that tackles action detection in multimodal videos
under a realistic and challenging condition in which only limited training data
and partially observed modalities are available. Common methods in transfer
learning do not take advantage of the extra modalities potentially available in
the source domain. On the other hand, previous work on multimodal learning only
focuses on a single domain or task and does not handle the modality discrepancy
between training and testing. In this work, we propose a method termed graph
distillation that incorporates rich privileged information from a large-scale
multimodal dataset in the source domain, and improves the learning in the
target domain where training data and modalities are scarce. We evaluate our
approach on action classification and detection tasks in multimodal videos, and
show that our model outperforms the state-of-the-art by a large margin on the
NTU RGB+D and PKU-MMD benchmarks. The code is released at
http://alan.vision/eccv18_graph/.Comment: ECCV 201
Collaboration in the Semantic Grid: a Basis for e-Learning
The CoAKTinG project aims to advance the state of the art in collaborative mediated spaces for the Semantic Grid. This paper presents an overview of the hypertext and knowledge based tools which have been deployed to augment existing collaborative environments, and the ontology which is used to exchange structure, promote enhanced process tracking, and aid navigation of resources before, after, and while a collaboration occurs. While the primary focus of the project has been supporting e-Science, this paper also explores the similarities and application of CoAKTinG technologies as part of a human-centred design approach to e-Learning
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