'Imagine an oak tree in a field of wheat, silhouetted against a cloudless blue sky on a dreamy sunny afternoon. The chances are that most people reading this sentence can easily picture a bucolic scene in their mind’s eye. This ability to read a description of a scene and then imagine it has always been uniquely human. But this precious skill may no longer be ours alone.
Anyone thinking that these kinds of imaginings are far beyond the ability of today’s computing machines will be surprised by the work of Hiroharu Kato and Tatsuya Harada at the University of Tokyo in Japan.
Today, these guys unveil a machine that can translate a description of an object into an image. In other words, their computer can conjure an image of an external object not otherwise present. That’s a pretty good definition of imagination—in this case of the computational variety.'
[1505.05190] Image Reconstruction from Bag-of-Visual-Words
'The objective of this work is to reconstruct an original image from Bag-of-Visual-Words (BoVW). Image reconstruction from features can be a means of identifying the characteristics of features. Additionally, it enables us to generate novel images via features. Although BoVW is the de facto standard feature for image recognition and retrieval, successful image reconstruction from BoVW has not been reported yet. What complicates this task is that BoVW lacks the spatial information for including visual words. As described in this paper, to estimate an original arrangement, we propose an evaluation function that incorporates the naturalness of local adjacency and the global position, with a method to obtain related parameters using an external image database. To evaluate the performance of our method, we reconstruct images of objects of 101 kinds. Additionally, we apply our method to analyze object classifiers and to generate novel images via BoVW. '