publication . Conference object . 2016

Deep Multi-task Learning with Label Correlation Constraint for Video Concept Detection

Bulterman, Dick; Markatopoulou, Foteini; Mezaris, Vasileios; Patras, Ioannis;
English
  • Published: 17 Oct 2016
  • Publisher: ACM Press
Abstract
In this work we propose a method that integrates multi-task learning (MTL) and deep learning. Our method appends a MTL-like loss to a deep convolutional neural network, in order to learn the relations between tasks together at the same time, and also incorporates the label correlations between pairs of tasks. We apply the proposed method on a transfer learning scenario, where our objective is to fine-tune the parameters of a network that has been originally trained on a large-scale image dataset for concept detection, so that it be applied on a target video dataset and a corresponding new set of target concepts. We evaluate the proposed method for the video conc...
Subjects
free text keywords: Concept detection; deep learning; video analysis, TRECVID, Correlation, Pattern recognition, Computer vision, Transfer of learning, Video annotation, Search engine indexing, Artificial intelligence, business.industry, business, Convolutional neural network, Machine learning, computer.software_genre, computer, Multi-task learning, Computer science, Deep learning
Funded by
EC| InVID
Project
InVID
In Video Veritas – Verification of Social Media Video Content for the News Industry
  • Funder: European Commission (EC)
  • Project Code: 687786
  • Funding stream: H2020 | IA
,
EC| MOVING
Project
MOVING
Training towards a society of data-savvy information professionals to enable open leadership innovation
  • Funder: European Commission (EC)
  • Project Code: 693092
  • Funding stream: H2020 | RIA
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publication . Conference object . 2016

Deep Multi-task Learning with Label Correlation Constraint for Video Concept Detection

Bulterman, Dick; Markatopoulou, Foteini; Mezaris, Vasileios; Patras, Ioannis;