Pytorch Pedestrian Attribute Recognition: A strong PyTorch baseline for pedestrian attribute recognition and multi-label classification
Rethinking of Pedestrian Attribute Recognition: A Reliable Evaluation under Zero-Shot Pedestrian Identity Setting (official Pytorch implementation)
This paper submitted to TIP is the extension of the previous Arxiv paper.
This project aims to
- provide a strong baseline for Pedestrian Attribute Recognition and Multi-Label Classification.
- provide two new datasets RAPzs and PETAzs following zero-shot pedestrian identity setting.
- provide a general training pipeline for pedestrian attribute recognition and multi-label classification task.
This project provide
- DDP training, which is mainly used for multi-label classifition.
- Training on all attributes, testing on “selected” attribute. Because the proportion of positive samples for other attributes is less than a threshold, such as 0.01.