[Nakamasa Inoue] Higher-Order Models for Semantic Concept Discovery on Multimedia Data

Researcher

Nakamasa Inoue

Nakamasa Inoue

Tokyo Institute of Technology
Department of Computer Science
Assistant Professor

Website

Outline

The goal of this project is to create higher-order models for discovering semantic concepts from multimedia data. Here, a higher-order model is a model to generate detection models for unseen semantic concepts such as objects, actions, and scenes. We develop a learning framework to obtain a higher-order model from pre-trained deep neural networks. We evaluate the framework on a large-scale video dataset by finding and detecting unseen objects, event and scenes.

Program

  • CREST
  • PRESTO
  • ACT-I
  • ERATO
  • ACT-C
  • ACCEL
  • ALCA
  • RISTEX
Finish programs
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  • GlobalActivity
  • Diversity-EN
  • OS_Policy-EN
  • Question-E