The invention provides systems and methods for detecting an object in an input image based on a target object keyword (e.g. people). A heat map 310a of the input image 306 is generated based on the target object keyword. Various bounding boxes 314a, based on a pixel analysis of the heat map, are then derived. One or more centre boxes 316a are then generated from the bounding boxes using local thresholds. Object location proposals 318a,b,c are also determined based on the keyword. The bounding boxes are then used to determine scores for the object location proposals and the box 318c for the highest scoring object location proposal is overlaid on the input image. The object location proposals could be derived using a YOLO algorithm. The heat map could be generated using a fully-convolutional dense tagging network. The method could also employ a weakly supervised model which avoids some of the costs of a learning process.
Detecting objects using a weakly supervised model