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Few-shot Font Generation with Weakly Supervised Localized Representations., , , , and . CoRR, (2021)Attention-Based Dropout Layer for Weakly Supervised Single Object Localization and Semantic Segmentation., , and . IEEE Trans. Pattern Anal. Mach. Intell., 43 (12): 4256-4271 (2021)Few-Shot Font Generation With Weakly Supervised Localized Representations., , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 46 (3): 1479-1495 (March 2024)Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts., , , , and . ICCV, page 13880-13889. IEEE, (2021)Rethinking the Truly Unsupervised Image-to-Image Translation., , , , and . ICCV, page 14134-14143. IEEE, (2021)Rethinking the Truly Unsupervised Image-to-Image Translation., , , , and . CoRR, (2020)Inverse lighting for non-homogeneous objects from color and depth image using wavelet representation., and . Computational Imaging, volume 9401 of SPIE Proceedings, page 94010L. IS&T/SPIE, (2015)Logit Mixing Training for More Reliable and Accurate Prediction., , , , , , , and . IJCAI, page 2812-2819. ijcai.org, (2022)Few-shot Font Generation with Localized Style Representations and Factorization., , , , and . CoRR, (2020)Resembled Generative Adversarial Networks: Two Domains with Similar Attributes., and . BMVC, page 224. BMVA Press, (2018)