Hifaface
Web29 de mar. de 2024 · We also notice that a fine-grained and wider-range control for the attribute is of great importance for face editing. To achieve this goal, we propose a novel attribute regression loss. Powered by the proposed framework, we achieve high-fidelity and arbitrary face editing, outperforming other state-of-the-art approaches. * CVPR 2024. Web29 de mar. de 2024 · Cycle consistency is widely used for face editing. However, we observe that the generator tends to find a tricky way to hide information from the original …
Hifaface
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WebFigure 14: Interpolation results on attribute “smile” obtained by RelGAN [35], InterFaceGAN(IFGAN) [31], HifaFace without the Lar and our HifaFace. - "High-Fidelity and Arbitrary Face Editing" Web1 de jan. de 2024 · The initial learning rate is 3 e − 4 and decayed by a factor of 0.1 every 10 epochs. For semantic face editing, we randomly generate face images on the fly with the pretrained generator. We use SGD with a momentum weight of 0.9, learning rate of 0.001 and batch size of 10 to train the modified generator.
Web6 de nov. de 2024 · For example, HiFaFace uses high-fidelity domain adversarial loss, and Nederhood et al. used the hinge version of the normal adversarial loss. Furthermore, the methods of this category use a wide range of discriminators. FacialGAN, inspired by StarGAN v2, uses a multitask discriminator. HifaFace proposed a high-frequency … Web29 de dez. de 2024 · Thanks for your interest. Due to the policy of the company, we can not release the source code of this paper. The core modules are listed in the supplementary materials. The WavePool, WaveUnpool, and their related modules are mainly adop...
Web27 de out. de 2024 · Facial editing has made remarkable progress with the development of deep neural networks [18, 19].More and more methods use the GANs to edit faces and generate images that utilize the image-to-image translation [21, 27] or embed into the GAN’s latent space [22, 29, 36, 37].Recent studies have shown that the StyleGAN2 contains … Web22 de dez. de 2024 · HifiFace — Unofficial Pytorch Implementation. Image source: HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping (figure 1, pg. 1) This …
Web29 de mar. de 2024 · In this work, we propose a simple yet effective method named HifaFace to address the above-mentioned problem from two perspectives. First, we …
WebSemantic Scholar profile for Yue Gao, with 28 highly influential citations and 8 scientific research papers. curl expression maskWeb15 de mar. de 2024 · in the field of the interpretability of generative adversarial. networks (GANs). This paper proposes a generic method to. modify a traditional GAN into an … curl extend timeoutCycle consistency is widely used for face editing. However, we observe that the generator tends to find a tricky way to hide information from the original image to satisfy the constraint of cycle consistency, making it impossible to maintain the rich details (e.g., wrinkles and moles) of non-editing areas. In this work, … Ver mais This is the project site of the High-Fidelity and Arbitrary Face Editing. Paper: arXiv Dataset: CelebaHQ FFHQ Ver mais Cycle consistency in CycleGANs causes steganography. The key idea of our method is to adopt a wavelet-based generator and a high-frequency discriminator. Ver mais curlex medical dressingWebPapers like VAEGAN[5], pSp[6], e4e[7], MaskFaceGAN[8], HifaFace[9], etc., provide us with methods and models to manipulate the output of generative models. Our work is based on a method called Cyclic Reverse Generator (CRG)[10]. These methods work by manipulating the input of image generation models to produce the desired image. curlex wattleWeb1 de jan. de 2024 · HifaFace (Gao et al., 2024) incorporates wavelet transformation to recover the rich details. Show abstract Although significant progress has been made in synthesizing high-quality and visually realistic face images by unconditional Generative Adversarial Networks (GANs), there is still a lack of control over the generation process … curlex with seedWebsuch as StarGAN [6] STGAN [26], HifaFace [11], and TediGAN [43] has enabled high fidelity image creation, or even enable interactive facial attribute editing. Identity swap methods generate fake videos by replacing the face . methods such as FaceSwap 1 and deep learning based methods like DeepFakes 2. The recent deep learning based … curl expression shampooWebCycle consistency is widely used for face editing. However, we observe that the generator tends to find a tricky way to hide information from the original image to satisfy the constraint of cycle consistency, making it impossible to maintain the rich details (e.g., wrinkles and moles) of non-editing areas. In this work, we propose a simple yet effective method … curlex straw blanket