Objects Localization Through CNN
Technically this is possible but most approaches combine localization with some sort of classification so that the network can get better at scoring regions, and also removes the problem of having to use the [0, 0, 0, 0] vector to encode a null region since if the classifier associated with the region gives a low probability for that object you can ignore the bounding box. That way the bounding box regression can focus on finding regions that look like they contain objects, not their type. Note that the classifier needs to be trained so that it recognizes a non-object region (ie, it must have a null/garbage/background class).

See for example:

Object localization and detection

Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks

(I don't have enough reputation to post more links but you should also google the R-CNN paper "Rich feature hierarchies for accurate object detection and semantic segmentation")