Deep learning has enabled the rapid expansion of computer vision tasks from image frames to video segments. This paper focuses on the review of the latest research in the field of computer vision tasks in general and on object localization and identification of their associated pixels in video frames in particular. After performing a systematic analysis of the existing methods, the challenges related to computer vision tasks are presented. In order to address the existing challenges, a hybrid framework is proposed, where deep learning methods are coupled with domain knowledge. An additional feature of this survey is that a review of the currently existing approaches integrating domain knowledge with deep learning techniques is presented. Finally, some conclusions on the implementation of hybrid architectures to perform computer vision tasks are discussed.