computer-vision-10
Face Sketch Synthesis
3260 papers • 126 benchmarks • 313 datasets
Face sketch synthesis is the task of generating a sketch from an input face photo. ( Image credit: High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks )
(Image credit: Papersgraph)
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Most implemented papers
TediGAN: Text-Guided Diverse Face Image Generation and Manipulation
Weihao Xia, Yujiu Yang, Jing Xue, Baoyuan Wu•Mon May 31 2021
In this work, we propose TediGAN, a novel framework for multi-modal image generation and manipulation with textual descriptions. The proposed method consists of three components: StyleGAN inversion module, visual-linguistic similarity learning, and instance-level optimization. The inversion module maps real images to the latent space of a well-trained StyleGAN. The visual-linguistic similarity learns the text-image matching by mapping the image and text into a common embedding space. The instancelevel optimization is for identity preservation in manipulation. Our model can produce diverse and high-quality images with an unprecedented resolution at 10242. Using a control mechanism based on style-mixing, our TediGAN inherently supports image synthesis with multi-modal inputs, such as sketches or semantic labels, with or without instance guidance. To facilitate text-guided multi-modal synthesis, we propose the Multi-Modal CelebA-HQ, a large-scale dataset consisting of real face images and corresponding semantic segmentation map, sketch, and textual descriptions. Extensive experiments on the introduced dataset demonstrate the superior performance of our proposed method. Code and data are available at https://github.com/weihaox/TediGAN.
