1. A method for training a pedestrian pose classification model, comprising: receiving a three-dimensional (3D) model of a pedestrian; for each of a plurality of training images of pedestrians, perform the following steps: receiving a set of image parameters indicating how to generate an image of a pedestrian and a pose classification of the pedestrian; generating a two-dimensional (2D) synthetic image based on the received 3D model and the received set of image parameters; annotating the generated synthetic image with the set of image parameters; and sequentially training a plurality of pedestrian pose classifiers through the annotated synthetic image, comprising: upon detecting that the pose classification of the pedestrian corresponds to a current pedestrian pose classifier, using the annotated synthetic image as a positive sample to train the current pedestrian pose classifier and using the annotated synthetic image as a negative sample to train the remaining pedestrian pose classifiers.