1. A system to recognize objects in an image, the system comprising: an object detection network to detect an object in an input image, the object detection network comprising a first hierarchical convolutional neural network to output a first hierarchical-calculated feature for the detected object; a face alignment regression network to determine a regression loss for alignment parameters based on the first hierarchical-calculated feature for the detected object; and a detection box regression network to determine a regression loss for detected boxes based on the first hierarchical-calculated feature for the detected object, wherein the object detection network further comprises: a weighted loss generator to generate a weighted loss for the first hierarchical-calculated feature for the detected object, the regression loss for the alignment parameters and the regression loss of the detected boxes; a backpropagator to backpropagate the generated weighted loss; and a grouping network to form, based on the first hierarchical-calculated feature for the detected object, the regression loss for the alignment parameters and the bounding box regression loss, at least one of a box grouping, an alignment parameter grouping, and a non-maximum suppression of the alignment parameters and the detected boxes.