现在每个人都可以签名吗？基于2D姿势的手语视频生成研究
Can Everybody Sign Now? Exploring Sign Language Video Generation from 2D Poses
摘要：
最近的工作已经解决了由用于手语的人体关节的2D/3D坐标表示的人体姿势的生成。我们使用深度学习中最先进的技术进行运动传输，并在美国手语数据集How2 Sign上对其进行评估，以生成签名者在给定2D姿势骨架的情况下执行手语的视频。我们对生成的视频进行了定量和定性评估，结果表明，由于缺乏手中的细节，目前的模型不足以生成足够的手语视频。
英文摘要：
Recent work have addressed the generation of human poses represented by 2D/3D coordinates of human joints for sign language. We use the state of the art in Deep Learning for motion transfer and evaluate them on How2Sign, an American Sign Language dataset, to generate videos of signers performing sign language given a 2D pose skeleton. We evaluate the generated videos quantitatively and qualitatively showing that the current models are not enough to generated adequate videos for Sign Language due to lack of detail in hands.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
