Blog

Learning RGB-D features for images and videos

Depth sensors capture information that complements conventional RGB data. How to combine them in an effective multimodal representation is still ...
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Mix and match networks

We recently explored how we can take multiple seen image-to-image translators and reuse them to infer other unseen translations, in ...
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Rotating networks to prevent catastrophic forgetting

In contrast to humans, neural networks tend to quickly forget previous tasks when trained on a new one (without revisiting ...
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Generative adversarial networks and image-to-image translation

Yet another post about generative adversarial networks (GANs), pix2pix and CycleGAN. You can already find lots of webs with great introductions to ...
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Deep network compression and adaptation

Network compression and adaptation are generally considered as two independent problems, with compressed networks evaluated on the same dataset, and ...
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