We propose a novel approach to animate human hair in a still portrait photo. Existing work has largely studied the animation of fluid elements such as water and fire. However, hair animation for a real image remains underexplored, which is a challenging problem, due to the high complexity of hair structure and dynamics. Considering the complexity of hair structure, we innovatively treat hair wisp extraction as an instance segmentation problem, where a hair wisp is referred to as an instance. With advanced instance segmentation networks, our method extracts meaningful and natural hair wisps. Furthermore, we propose a wisp-aware animation module that animates hair wisps with pleasing motions without noticeable artifacts. The extensive experiments show the superiority of our method. Our method provides the most pleasing and compelling viewing experience in the qualitative experiments and outperforms state-of-the-art still-image animation methods by a large margin in the quantitative evaluation. Project url: \url{https://nevergiveu.github.io/AutomaticHairBlowing/}

翻译：我们提出了一种新颖的方法，用于在静态肖像照片中实现人类头发的动画化。现有工作主要研究了水、火等流体元素的动画化，然而，针对真实图像中头发动画的研究尚不充分，这是一个具有挑战性的问题，原因是头发结构和动力学的高度复杂性。考虑到头发结构的复杂性，我们创新性地将发丝提取视为一个实例分割问题，其中每一缕发丝被视为一个实例。借助先进的实例分割网络，我们的方法能够提取出有意义且自然的发丝。此外，我们还提出了一种发丝感知动画模块，该模块能够以令人愉悦的运动方式动画化发丝，且不产生明显伪影。大量实验表明了我们方法的优越性。在定性实验中，我们的方法提供了最令人愉悦且引人入胜的观看体验，并在定量评估中大幅超越了最先进的静态图像动画方法。项目网址：\url{https://nevergiveu.github.io/AutomaticHairBlowing/}