Close-up facial images captured at close distances often suffer from perspective distortion, resulting in exaggerated facial features and unnatural/unattractive appearances. We propose a simple yet effective method for correcting perspective distortions in a single close-up face. We first perform GAN inversion using a perspective-distorted input facial image by jointly optimizing the camera intrinsic/extrinsic parameters and face latent code. To address the ambiguity of joint optimization, we develop focal length reparametrization, optimization scheduling, and geometric regularization. Re-rendering the portrait at a proper focal length and camera distance effectively corrects these distortions and produces more natural-looking results. Our experiments show that our method compares favorably against previous approaches regarding visual quality. We showcase numerous examples validating the applicability of our method on portrait photos in the wild.

翻译：近距离拍摄的人脸图像常因透视畸变导致面部特征夸张、外观不自然。我们提出了一种简单有效的方法，可对单张近距离人脸图像进行透视畸变校正。首先，通过联合优化相机内/外参数与人脸隐编码，对透视畸变输入人脸图像执行GAN逆映射。为解决联合优化的歧义性，我们设计了焦距重参数化、优化调度与几何正则化策略。通过以恰当的焦距与相机距离重新渲染人像，可有效校正畸变并生成更自然的结果。实验表明，我们的方法在视觉质量上优于现有方法。大量野外场景人像照片的校正实例验证了本方法的实用性。