论文标题
无心的人：将自拍照转化为野外中立姿势的肖像
Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild
论文作者
论文摘要
由于智能手机的普遍存在，拍摄自己的自我或“自拍照”是很受欢迎的。这样的照片很方便，因为它们不需要专业设备或第三方摄影师。但是，在自拍照中，诸如人臂长度之类的约束通常会使身体姿势看起来不自然。为了解决这个问题，我们介绍了$ \ textit {unselfie} $，这是一种新颖的摄影转换，将自拍照自动转化为中性姿势肖像。为了实现这一目标，我们首先收集一个未配对的数据集，并引入一种合成配对培训数据以进行自我监督学习的方法。然后，到$ \ textit {unfellie} $一张照片，我们提出了一条新的三阶段管道，我们首先找到了目标中性姿势，对身体质地进行涂漆，最后完善并在后台进行了复合。为了获得合适的目标中性姿势，我们提出了一个新颖的姿势搜索模块，该模块使安息任务变得更加容易，并可以生成多个中性置姿势结果，其中用户可以选择他们喜欢的最佳选择。定性和定量评估表明，我们的管道优于替代方案。
Due to the ubiquity of smartphones, it is popular to take photos of one's self, or "selfies." Such photos are convenient to take, because they do not require specialized equipment or a third-party photographer. However, in selfies, constraints such as human arm length often make the body pose look unnatural. To address this issue, we introduce $\textit{unselfie}$, a novel photographic transformation that automatically translates a selfie into a neutral-pose portrait. To achieve this, we first collect an unpaired dataset, and introduce a way to synthesize paired training data for self-supervised learning. Then, to $\textit{unselfie}$ a photo, we propose a new three-stage pipeline, where we first find a target neutral pose, inpaint the body texture, and finally refine and composite the person on the background. To obtain a suitable target neutral pose, we propose a novel nearest pose search module that makes the reposing task easier and enables the generation of multiple neutral-pose results among which users can choose the best one they like. Qualitative and quantitative evaluations show the superiority of our pipeline over alternatives.
