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dc.date.accessioned | 2023-04-19T14:57:38Z | |
dc.date.available | 2023-04-19T14:57:38Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | http://sedici.unlp.edu.ar/handle/10915/151735 | |
dc.description.abstract | During recent years transformers architectures have been growing in popularity. Modulated Detection Transformer (MDETR) is an end-to-endmulti-modal understanding model that performs tasks such as phase grounding, referring expression comprehension, referring expression segmentation, andvisual question answering. One remarkable aspect of the model is the capacity to infer over classes that it was not previously trained for. In this work we explore the use of MDETR in a new task, action detection, without any previous training. We obtain quantitative results using the Atomic Visual Actions dataset.Although the model does not report the best performance in the task, we believe that it is an interesting finding. We show that it is possible to use a multi-modal model to tackle a task that it was not designed for. Finally, we believe that this line of research may lead into the generalization of MDETR in additionaldownstream tasks. | en |
dc.format.extent | 6-10 | es |
dc.language | en | es |
dc.subject | Multi-modal transformers | es |
dc.subject | Action detection | es |
dc.subject | Model generalization | es |
dc.title | Exploring modulated detection transformer as a tool for action recognition in videos | en |
dc.type | Objeto de conferencia | es |
sedici.identifier.uri | https://publicaciones.sadio.org.ar/index.php/JAIIO/article/download/388/326 | es |
sedici.identifier.issn | 2451-7496 | es |
sedici.creator.person | Crisol, Tomás | es |
sedici.creator.person | Ermantraut, Joel | es |
sedici.creator.person | Rostagno, Adrián | es |
sedici.creator.person | Aggio, Santiago L. | es |
sedici.creator.person | Iparraguirre, Javier | es |
sedici.subject.materias | Ciencias Informáticas | es |
sedici.description.fulltext | true | es |
mods.originInfo.place | Sociedad Argentina de Informática e Investigación Operativa | es |
sedici.subtype | Objeto de conferencia | es |
sedici.rights.license | Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) | |
sedici.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
sedici.date.exposure | 2022-10 | |
sedici.relation.event | Simposio Argentino de Imágenes y Visión (SAIV 2022) - JAIIO 51 (Modalidad virtual y presencial (UAI), octubre 2022) | es |
sedici.description.peerReview | peer-review | es |