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A display of our dramatic yet mesmerizing failures training ClimateGAN

Do not underestimate the output of a faulty model.

This website gathers creative yet unvoluntary visual findings along our two years of research creating ClimateGAN.

A storm of pixels. Can you survive Hurricane Colora?

These images result from a faulty post-processing, rescaling [0; 1] pixels as if they were [0; 255].

Virtual Pointillism.

A segmentation model can be creative too you know? Especially if you train it with the wrong loss.

Saturation is all you need.

GANs are unstable beasts. They tend to collapse, and God knows where they land when you forget the discriminator.

Stumbling upon your own failures can lift your spirits, when you are open to surprises.

A random collection of failures and accidents in our quest for depth maps.

Logging is a timber's burden

There's a dark forest of traps ahead: axing your way through model comparison and multi-modal visual outputs plotting is a journey in itself.

GANs breathe too. Their heartbeats soothe the soul.

Forwarding a series of noise images through a GauGAN non-trained (just initialized) model. When the center pixel is artificially boosted, the model naturally focuses on that part of the noise, creating this narrower and narrower output circle.