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Affective Image Manipulation (AIM) aims to alter visual elements within an image to evoke specific emotional responses from viewers.
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Z. Xu and S. Wang, “Emotional attention detection and correlation exploration for image emotion distribution learning,” IEEE Transactions on Affective Computing , vol. 14, no. 01, pp. 357–369, 2023
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2024
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Q. Mao, L. Chen, Y. Gu, Z. Fang, and M. Z. Shou, “Mag-edit: Localized image editing in complex scenarios via mask-based attention-adjusted guidance,” in ACM International Conference on Multimedia , 2024
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H. Xie, C.-J. Peng, Y.-W. Tseng, H.-J. Chen, C.-F. Hsu, H.-H. Shuai, and W.-H. Cheng, “Emovit: Revolutionizing emotion insights with visual instruction tuning,” in CVPR , 2024
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J. Yang, J. Feng, W. Luo, D. Lischinski, D. Cohen-Or, and H. Huang, “Emoedit: Evoking emotions through image manipulation,” in CVPR , 2025
2025
Closest in time.
2025
Closest in time.