  An "elephant in the room" for most current object detection and localization
methods is the lack of explicit modelling of partial visibility due to
occlusion by other objects or truncation by the image boundary. Based on a
sliding window approach, we propose a detection method which explicitly models
partial visibility by treating it as a latent variable. A novel non-maximum
suppression scheme is proposed which takes into account the inferred partial
visibility of objects while providing a globally optimal solution. The method
gives more detailed scene interpretations than conventional detectors in that
we are able to identify the visible parts of an object. We report improved
average precision on the PASCAL VOC 2010 dataset compared to a baseline
detector.
