Abstract
In this paper, we first tackle the problem of pedestrian attribute recognition by video-based approach.The challenge mainly lies in spatial and temporal modeling and how to integrating them for effective and dynamic pedestrian representation.To solve this problem, a novel deep recurrent neural network with hybrid pooling strategy is proposed.Since publicly available dataset is rare, a new large-scale video dataset for pedestrian attribute recognition is annotated, on which the effectiveness of both video-based pedestrian attribute recognition and the proposed new network architecture is well demonstrated.
Abstract (translated by Google)
URL
https://arxiv.org/abs/1901.05742