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Bi-level Feature Alignment for Versatile Image Translation and Manipulation. (arXiv:2107.03021v2 [cs.CV] UPDATED)
July 25, 2022, 1:13 a.m. | Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Kaiwen Cui, Aoran Xiao, Shijian Lu, Chunyan Miao
cs.CV updates on arXiv.org arxiv.org
Generative adversarial networks (GANs) have achieved great success in image
translation and manipulation. However, high-fidelity image generation with
faithful style control remains a grand challenge in computer vision. This paper
presents a versatile image translation and manipulation framework that achieves
accurate semantic and style guidance in image generation by explicitly building
a correspondence. To handle the quadratic complexity incurred by building the
dense correspondences, we introduce a bi-level feature alignment strategy that
adopts a top-$k$ operation to rank block-wise features …
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