Attribute Recognition from Adaptive Parts

نویسندگان

  • Luwei Yang
  • Ligen Zhu
  • Yichen Wei
  • Shuang Liang
  • Ping Tan
چکیده

Previous part-based attribute recognition approaches perform part detection and attribute recognition in separate steps. The parts are not optimized for attribute recognition and therefore could be sub-optimal. We present an end-to-end deep learning approach to overcome the limitation. It generates object parts from key points and perform attribute recognition accordingly, allowing adaptive spatial transform [10] of the parts. Both key point estimation and attribute recognition are learnt jointly in a multi-task setting. Extensive experiments on two datasets verify the efficacy of proposed end-to-end approach.

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عنوان ژورنال:
  • CoRR

دوره abs/1607.01437  شماره 

صفحات  -

تاریخ انتشار 2016