🍊 The Juice: Define Sandwich

Zumo Labs presents The Juice, a weekly newsletter focused on computer vision problems (and sometimes just regular problems). Get it while it’s fresh.

Week of February 8–12, 2021

What is a sandwich? Maybe you’ve heard this one before, but try to define a sandwich. Odds are good that one of your more annoying friends would be able to suggest something that, yes, upon closer examination, is technically a sandwich. (“What about open-faced sandwiches? Hoagies? Hot dogs? A folded slice of pizza?”) The point of the prompt is to show that, as humans, we have trouble with this sort of classification exercise.

But it’s not so much that we’re bad at classification — we seem to demonstrate a good intuitive sense of what’s what — as it is the sloppy mess of labels for the things in our everyday life. And if messy labels can trip us up, you can imagine what they do to a computer vision model. We advocate for synthetic data a lot and, while it’s not a silver bullet, it does resolve a lot of the issues of the industry standard that it’s intended to supplement (or in some cases, replace): sourced labeled data. It’s a topic we covered in our most recent blog post, Five Big Problems With Labeled Data.

Gosh, how would you even begin to train a computer vision model to detect a sandwich? No idea, but if you’ll excuse us, we made ourselves hungry.



Researchers find that labels in computer vision datasets poorly capture racial diversity, via VentureBeat.


This is how we lost control of our faces, via MIT Technology Review.


Lawsuit alleges Apple biometrics infringe patents, via Biometric Update.


Scientists prove that deepfake detectors can be duped, via Engadget.

An illustration of how a computer vision system can automaticall power a hydraulic lift platform for apple pickers.
An illustration of how a computer vision system can automaticall power a hydraulic lift platform for apple pickers.


Alternative Weed Control — We’ll Have An App For That, via NC State University.

Collaborative robotics tested in tree fruit, via Good Fruit Grower.


Kitten Zoom Filter Mishap, via YouTube.


📄 Paper of the Week

Using a GAN to style transfer the appearance of real images onto synthetic images is a key component of the synthetic data creation toolkit. This paper proposes a variation they call the “GAN-Reskinner”, where a GAN generates the texture that is applied to a 3D model (rather than being applied to the final image itself). They demonstrate the effectiveness of their new approach on a satellite image detection task.


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ml & cv enthusiast, works at zumolabs.ai