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We introduce a new method for diverse foreground generation with explicit control over various factors.
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Karras, T., Laine, S., Aila, T.: A style-based generator architecture for generative adversarial networks. In: CVPR (2019)
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Lee, C.H., Liu, Z., Wu, L., Luo, P.: Maskgan: Towards diverse and interactive facial image manipulation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
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Singh, K.K., Ojha, U., Lee, Y.J.: Finegan: Unsupervised hierarchical disentanglement for fine-grained object generation and discovery. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) pp. 6483–6492 (2019)
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Xiong, W., Yu, J., Lin, Z.L., Yang, J., Lu, X., Barnes, C., Luo, J.: Foreground-aware image inpainting. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) pp. 5833–5841 (2019)
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Shen, Y., Gu, J., Tang, X., Zhou, B.: Interpreting the latent space of gans for semantic face editing. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) pp. 9240–9249 (2020)
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Guo, X., Yang, H., Huang, D.: Image inpainting via conditional texture and structure dual generation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 14134–14143 (October 2021)
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Suin, M., Purohit, K., Rajagopalan, A.N.: Distillation-guided image inpainting. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 2481–2490 (October 2021)
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Yu, Y., Zhan, F., Wu, R., Pan, J., Cui, K., Lu, S., Ma, F., Xie, X., Miao, C.: Diverse image inpainting with bidirectional and autoregressive transformers. Proceedings of the 29th ACM International Conference on Multimedia (2021)
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Zhou, X., Li, J., Wang, Z., He, R., Tan, T.: Image inpainting with contrastive relation network. 2020 25th International Conference on Pattern Recognition (ICPR) pp. 4420–4427 (2021)
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