My last post demonstrated a simple process for evaluating a set of face pairs to determine whether or not the two are blood relatives. Several snippets were breezed over like black-boxes. Let us look at one of my those snippets, a simple 1-liner: a Python Pandas feature I recently learned, and now use frequently.
The top of the table contains the positive pairs, while the bottom is the negatives. See the differences in scores. As we would hope, the KIN pairs seem to score higher (i.e., be more similar) than that of the NON-KIN. In most cases, the labels get loaded from a separate file.
Pycharm, for me, is a great IDE - complete with features that promote productive programming, a community devoted to sharing clever plug-ins, and, my personal favorite trait, Professional licenses are free to students. With this, JetBrains toolbox with its many IDEs (one for most modern computing language) is available to students free of charge (no strings attached).
The new components of RFIW2020 are listed as follows: Three Challenges : two new tracks, and the return of kinship verification. General Papers : call for papers in work in automatic kinship recognition. Brave New Idea : call for innovative ways of viewing the problem.
Our paper - FR: Too bias, or Not Too Bias? - is being published as part of The Workshop of Fair, Data-Efficient, and Trusted Computer Vision held in conjunction with the 2020 Conference on Computer Vision and Pattern Recognition (CVPR).
I stumbled upon Medium a few months ago - initially, I found the content broad in scope and material keen on quality - already there have been significant improvements found in blogs and overall interface.
