Where Is The Emotion? Dissecting A Multi-Gap Network For Image Emotion Classification


Lim, Lucinda and Khor, Huai Qian and Chaemchoy, Phatcharawat and See, John Su Yang and Wong, Lai Kuan (2020) Where Is The Emotion? Dissecting A Multi-Gap Network For Image Emotion Classification. In: 2020 IEEE International Conference on Image Processing (ICIP), 25-28 Oct. 2020, Virtual, Abu Dhabi, UAE.

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Image emotion recognition has become an increasingly popular research domain in the area of image processing and affective computing. Despite fast-improving classification performance in this task, the understanding and interpretability of its performance are still lacking as there are limited studies on which part of an image would invoke a particular emotion. In this work, we propose a Multi-GAP deep neural network for image emotion classification, which is extensible to accommodate multiple streams of information. We also incorporate feature dependency into our network blocks by adding a bidirectional GRU network to learn transitional features. We report extensive results on the variants of our proposed network and provide valuable perspectives into the class-activated regions via Grad-CAM, and network depth contributions by truncation strategy

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Neural networks (Computer science), Image emotion classification, multi-GAP, CNN, visualizations, class activation maps
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 10 Sep 2021 15:16
Last Modified: 10 Sep 2021 15:16
URII: http://shdl.mmu.edu.my/id/eprint/8519


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