Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond
Abstract. 最早进的行人检测模型在许多基准测试中取得了巨大的成功。然而，这些模型须要大量的注释信息，标记过程一般须要花费大量的时间和精力。本文提出了一种生成标记行人数据的方法，并将其用于行人检测器的训练。该框架创建在具备多个鉴别器的生成对抗网络(GAN)的基础上，试图对真实行人进行综合，同时学习背景信息。为了处理不一样大小的行人，咱们在鉴别器中采用了空间金字塔池(SPP)层。咱们在两个基准
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相关文章
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- 10. 人群运动--Scene-Independent Group Profiling in Crowd