DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwon, Oh Chul | ko |
dc.contributor.author | Kim, Junyeong | ko |
dc.contributor.author | Yoo, Chang-Dong | ko |
dc.date.accessioned | 2018-12-20T02:03:00Z | - |
dc.date.available | 2018-12-20T02:03:00Z | - |
dc.date.created | 2018-11-30 | - |
dc.date.created | 2018-11-30 | - |
dc.date.created | 2018-11-30 | - |
dc.date.issued | 2018-10-10 | - |
dc.identifier.citation | 2018 25th IEEE International Conference on Image Processing (ICIP), pp.3453 - 3457 | - |
dc.identifier.uri | http://hdl.handle.net/10203/247329 | - |
dc.description.abstract | This paper considers a 3D convolutional neural network (CNN) that learns spatial and temporal regions of higher importance through a bi-direction long short-term memory (bi-LSTM) attention for action recognition. First- and second-order differences of spatially most relevant C3D features (sp-m-C3D) are obtained, and the concatenation of the two differences with the sp-m-C3D is used to generate a temporal attention on the sp-m-C3D using a bi-LSTM. Temporally most relevant sp-m-C3D features are fed into another bi-LSTM for action recognition. Essentially, the network learns spatial and temporal regions of high importance for action recognition. We evaluate the network on two public action recognition datasets: UCF-101 (YouTube Action) and HMDB51. The proposed network performs better compared to other state-of-the-art networks. | - |
dc.language | English | - |
dc.publisher | IEEE | - |
dc.title | Action Recognition: First-and Second-Order 3D Feature in Bi-Directional Attention Network | - |
dc.type | Conference | - |
dc.identifier.wosid | 000455181503114 | - |
dc.identifier.scopusid | 2-s2.0-85062920663 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 3453 | - |
dc.citation.endingpage | 3457 | - |
dc.citation.publicationname | 2018 25th IEEE International Conference on Image Processing (ICIP) | - |
dc.identifier.conferencecountry | GR | - |
dc.identifier.conferencelocation | Athens International Conference Centre | - |
dc.identifier.doi | 10.1109/icip.2018.8451493 | - |
dc.contributor.localauthor | Yoo, Chang-Dong | - |
dc.contributor.nonIdAuthor | Kwon, Oh Chul | - |
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