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'Deepfake' technology used to advance autonomous vehicles

The technology makes it possible to reproduce the same scene in poor or adverse conditions

Developed by UK autonomous vehicle software specialist Oxbotica, the technology is capable of generating thousands of photo-realistic images in minutes to help test driverless vehicles safely.

UK-based autonomous vehicle software specialist Oxbotica has developed and deployed a “deepfake” technology that is capable of generating thousands of photo-realistic images in minutes.

It said this helps to expose its autonomous vehicles to “near infinite variations” of the same situation without real-world testing of a location.

Use of deepfaking

Deepfaking has been used to create viral internet videos and employs deep learning artificial intelligence (AI) to generate fake photo-realistic images.

The AV software firm believes that the technology will make the vehicles of tomorrow smarter and safer, and help to accelerate the shift to autonomy.

The algorithms used in the technology allow Oxbotica to reproduce the same scene in poor weather or adverse conditions, and subject its vehicles to rare occurrences.

It can reverse road signage or “class switch”, where one object, such as a tree, is replaced with another, for example, a building. It can change the lighting of an image, to show a particular frame at a different time of the day or season of the year, all while ensuring shadows or reflections appear exactly as they should.

It then uses these synthetic images to teach its software, producing thousands of accurately labelled, true-to-life experiences and rehearsals which are not real but generated, even down to the rain drops on lenses.

“Using deepfakes is an incredible opportunity for us to increase the speed and efficiency of safely bringing autonomy to any vehicle in any environment – a central focus of our Universal Autonomy vision,” said Paul Newman, co-founder and chief technology officer, Oxbotica. “What we’re really doing here is training our AI to produce a syllabus for other AIs to learn from. It’s the equivalent of giving someone a fishing rod rather than a fish. It offers remarkable scaling opportunities.

Read more

Originally published by
SmartCitiesWorld news team | June 25, 2020
Smart Cities World


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