
Large-Scale Long-Tailed Recognition in an Open World - headalgorithm
https://bair.berkeley.edu/blog/2019/05/13/oltr/
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iandanforth
This is interesting but suffers from not being written by native speakers. For
example this section is unclear

"Firstly, we obtain a visual memory by aggregating the knowledge from both
head and tail classes. Then the visual concepts stored in the memory are
infused back as associated memory feature to enhance the original direct
feature. It can be understood as using induced knowledge (i.e. memory feature)
to assist the direct observation (i.e. direct feature)."

What is a "visual memory?" Are they talking about a learned feature space? An
architecture isn't even mentioned. The word "infused" is used repeatedly in
the post but isn't well defined. Do they mean that there is a concatenation of
vectors? Or, from the diagram, is there an attentional weighting mechanism in
play?

I'm sure I'll understand more when I read the paper, but this blog post
doesn't have the intended effect reaching a broader audience through the use
of plain language.

