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20 de jul. de 2022 · The official repo for CM-GAN (Cascaded Modulation GAN) for Image Inpainting. We introduce a new cascaded modulation design that cascades global modulation with spatial adaptive modulation for better hole filling.
22 de mar. de 2022 · CM-GAN: Image Inpainting with Cascaded Modulation GAN and Object-Aware Training. Haitian Zheng, Zhe Lin, Jingwan Lu, Scott Cohen, Eli Shechtman, Connelly Barnes, Jianming Zhang, Ning Xu, Sohrab Amirghodsi, Jiebo Luo. Recent image inpainting methods have made great progress but often struggle to generate plausible image structures ...
14 de mar. de 2022 · Instead of modeling this complex domain with a single GAN, we propose a novel method to combine multiple pretrained GANs, where one GAN generates a global canvas (e.g., human body) and a set of specialized GANs, or insets, focus on different parts (e.g., faces, shoes) that can be seamlessly inserted onto the global canvas.
InsetGAN — Official PyTorch implementation. InsetGAN for Full-Body Image Generation. Anna Frühstück, Krishna Kumar Singh, Eli Shechtman, Niloy Mitra, Peter Wonka, Jingwan Lu. published at CVPR 2022. Project Webpage. Abstract While GANs can produce photo-realistic images in ideal conditions for certain domains, the generation of full-body ...
Instead of modeling this complex domain with a single GAN, we propose a novel method to combine multiple pretrained GANs, where one GAN generates a global canvas (e.g., human body) and a set of specialized GANs, or insets, focus on different parts (e.g., faces, shoes) that can be seamlessly inserted onto the global canvas.
Publication date: June 19, 2022. Anna Frühstück, Krishna Kumar Singh, Eli Shechtman, Niloy J. Mitra, Peter Wonka, Jingwan (Cynthia) Lu. While GANs can produce photo-realistic images in ideal conditions for certain domains, the generation of full-body human images remains difficult due to the diversity of identities, hairstyles, clothing, and ...
22 de mar. de 2022 · 2024. TLDR. This paper sort existing methods for image and video inpainting into different categories from the perspective of their high-level inpainting pipeline, present different deep learning architectures, including CNN, VAE, GAN, diffusion models, etc., and summarize techniques for module design. Expand.
