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EmoMV: Affective music-video correspondence learning datasets for classification and retrieval

  • Published:2023-03 Issue: Volume:91 Page:64-79
  • ISSN:1566-2535
  • Container-title:Information Fusion
  • language:en
  • Short-container-title:Information Fusion

Author:

Thao Ha Thi Phuong,Roig Gemma,Herremans DorienORCID

Funder

Government of Singapore Ministry of Education

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Signal Processing,Software

Reference102 articles.

1. Deep audio-visual learning: A survey;Zhu;Int. J. Autom. Comput.,2021

2. Look, listen and learn;Arandjelovic,2017

3. Cross-modal embeddings for video and audio retrieval;Surís,2018

4. Emotion-based end-to-end matching between image and music in valence-arousal space;Zhao,2020

5. Query by video: Cross-modal music retrieval;Li,2019

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1. Acoustic-articulatory emotion recognition using multiple features and parameter-optimized cascaded deep learning network;Knowledge-Based Systems;2024-01

2. Deformer: Denoising Transformer for Improved Audio Music Genre Classification;Applied Sciences;2023-11-25

3. EMID: An Emotional Aligned Dataset in Audio-Visual Modality;Proceedings of the 1st International Workshop on Multimedia Content Generation and Evaluation: New Methods and Practice;2023-10-29

4. YuYin: a multi-task learning model of multi-modal e-commerce background music recommendation;EURASIP Journal on Audio, Speech, and Music Processing;2023-10-19

5. MERP: A Music Dataset with Emotion Ratings and Raters’ Profile Information;Sensors;2022-12-29
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