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Xu, Xing (author), Lin, Kaiyi (author), Yang, Yang (author), Hanjalic, A. (author), Shen, Heng Tao (author)
Recently, generative adversarial network (GAN) has shown its strong ability on modeling data distribution via adversarial learning. Cross-modal GAN, which attempts to utilize the power of GAN to model the cross-modal joint distribution and to learn compatible cross-modal features, is becoming the research hotspot. However, the existing cross...
journal article 2022
document
Wang, Bokun (author), Yang, Yang (author), Xing, Xu (author), Hanjalic, A. (author), Shen, Heng Tao (author)
Cross-modal retrieval aims to enable flexible retrieval experience across different modalities (e.g., texts vs. images). The core of crossmodal retrieval research is to learn a common subspace where the items of different modalities can be directly compared to each other. In this paper, we present a novel Adversarial Cross-Modal Retrieval ...
conference paper 2017