Sequence-based Person Attribute Recognition with Joint CTC-Attention Model

Understand

Attribute recognition has become crucial because of its wide applications in many computer vision tasks, such as person re-identification.

• Like many object recognition problems, variations in viewpoints, illumination, and recognition at far distance, all make this task challenging.
• In this work, we propose a joint CTC-Attention model (JCM), which maps attribute labels into sequences to learn the semantic relationship among attributes.
• Besides, this network uses neural network to encode images into sequences, and employs connectionist temporal classification (CTC) loss to train the network with the aim of improving the encoding performance of the network.