论文标题
视觉变压器：艺术和研究的挑战
Vision Transformers: State of the Art and Research Challenges
论文作者
论文摘要
变形金刚在自然语言处理方面取得了巨大的成功。由于自我发挥机制在变压器中具有强大的能力，研究人员为各种计算机视觉任务（例如图像识别，对象检测，图像分割，姿势估计和3D重建）开发了视觉变压器。本文介绍了有关视觉变形金刚的不同建筑设计和培训技巧（包括自学学习）文献的全面概述。我们的目标是通过开放研究机会提供系统的审查。
Transformers have achieved great success in natural language processing. Due to the powerful capability of self-attention mechanism in transformers, researchers develop the vision transformers for a variety of computer vision tasks, such as image recognition, object detection, image segmentation, pose estimation, and 3D reconstruction. This paper presents a comprehensive overview of the literature on different architecture designs and training tricks (including self-supervised learning) for vision transformers. Our goal is to provide a systematic review with the open research opportunities.
