  The field of Weakly Supervised Learning (WSL) has recently seen a surge of
popularity, with numerous papers addressing different types of "supervision
deficiencies". In WSL use cases, a variety of situations exists where the
collected "information" is imperfect. The paradigm of WSL attempts to list and
cover these problems with associated solutions. In this paper, we review the
research progress on WSL with the aim to make it as a brief introduction to
this field. We present the three axis of WSL cube and an overview of most of
all the elements of their facets. We propose three measurable quantities that
acts as coordinates in the previously defined cube namely: Quality,
Adaptability and Quantity of information. Thus we suggest that Biquality
Learning framework can be defined as a plan of the WSL cube and propose to
re-discover previously unrelated patches in WSL literature as a unified
Biquality Learning literature.
