Open Access
Issue |
ITM Web Conf.
Volume 40, 2021
International Conference on Automation, Computing and Communication 2021 (ICACC-2021)
|
|
---|---|---|
Article Number | 03013 | |
Number of page(s) | 8 | |
Section | Computing | |
DOI | https://doi.org/10.1051/itmconf/20214003013 | |
Published online | 09 August 2021 |
- L. Gonog and Y. Zhou, “A Review: Generative Adversarial Networks,” 2019 14th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp. 505–510, (2019) [Google Scholar]
- P. Hurtik and P. Hodakova, “FTIP: A tool for an image plagiarism detection,” 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR), Fukuoka, Japan, pp. 42–47, (2015) [Google Scholar]
- Y. Lang, Y. He, F. Yang, J. Dong, H. Xue, “Which is Plagiarism: Fashion Image Retrieval based on Regional Representation for Design Protection,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2595–2604, (2020) [Google Scholar]
- Y. J. Cao, L. L. Jia, Y. X. Chen, N. Lin, C. Yang, B. Zhang, Z. Liu, X. X. Li, H. H. Dai, “Recent Advances of Generative Adversarial Networks in Computer Vision,” in IEEE Access, vol. 7, pp. 14985–15006, (2019) [Google Scholar]
- T. Xu, P. Zhang, Q. Huang, H. Zhang, Z. Gan, X. Huang, X. He, “AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks,” 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 1316–1324, (2018) [Google Scholar]
- I. J. Goodfellow, J. P. Abadie, M. Mirza, B. Xu, D. W. Farley, S. Ozair, A. Courville, Y. Bengio, “Generative Adversarial Nets,” arXiv preprint arXiv:1406.2661, vol: 1, (2014) [Google Scholar]
- K. Ak, A. Kassim, J. Lim and J. Y. Tham, “Attribute Manipulation Generative Adversarial Networks for Fashion Images,” 2019 IEEE/CVF International Conference on Computer Vision (ICCV), pp. 10540–10549, (2019) [Google Scholar]
- I. Amerini, L. Galteri, R. Caldelli and A. Del Bimbo, “Deepfake Video Detection through Optical Flow Based CNN,” 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 1205–1207, (2019) [Google Scholar]
- M. Chen, Y. Qin, L. Qi and Y. Sun, “Improving Fashion Landmark Detection by Dual Attention Feature Enhancement,” 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 3101–3104, (2019) [Google Scholar]
- N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), vol: 1, pp. 886–893, (2005) [Google Scholar]
- K. E. Ak, J. H. Lim, J. Y. Tham and A. A. Kassim, “Efficient Multi-attribute Similarity Learning Towards Attribute-Based Fashion Search,” 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1671–1679, (2018) [Google Scholar]
- H. Zhang, T. Xu, H. Li, S. Zhang, X. Wang, X. Huang and D. Metaxas, “StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks,” 2017 IEEE International Conference on Computer Vision (ICCV), 2017, pp. 5908–5916, (2017) [Google Scholar]
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