Taekeun Hong
- Peter Anderson, Xiaodong He, Chris Buehler, Damien Teney, Mark Johnson, Stephen Gould, and Lei Zhang. 2018. Bottom-up and top-down attention for image captioning and visual question answering. In Proceedings of the IEEE conference on computer vision and pattern recognition. 6077–6086.Google Scholar
Cross Ref
- Yang Chen, Yu-Kun Lai, and Yong-Jin Liu. 2018. Cartoongan: Generative adversarial networks for photo cartoonization. In Proceedings of the IEEE conference on computer vision and pattern recognition. 9465–9474.Google ScholarCross Ref
- Licheng Jiao and Jin Zhao. 2019. A Survey on the New Generation of Deep Learning in Image Processing. IEEE Access 7 (2019), 172231–172263.Google ScholarCross Ref
- Yitong Li, Zhe Gan, Yelong Shen, Jingjing Liu, Yu Cheng, Yuexin Wu, Lawrence Carin, David Carlson, and Jianfeng Gao. 2019. Storygan: A sequential conditional gan for story visualization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 6329–6338.Google ScholarCross Ref
- Jonghwan Mun, Minsu Cho, and Bohyung Han. 2020. Local-Global Video-Text Interactions for Temporal Grounding. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 10810–10819.Google ScholarCross Ref
- Alec Radford, Luke Metz, and Soumith Chintala. 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 (2015).Google Scholar
- Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio. 2015. Show, attend and tell: Neural image caption generation with visual attention. In International conference on machine learning. 2048–2057. Google ScholarDigital Library
- Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris N Metaxas. 2017. Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks. In Proceedings of the IEEE international conference on computer vision. 5907–5915.Google ScholarCross Ref
Index Terms
- A Text-to-Dynamic Image Generation Method using Feature Information of Video
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