![]() “After the training was completed, we used the same model for both shots with success.” “I generated a random dataset from both shots,” Johannes tells us. In these, the team cropped and tracked Kiyan’s shirt rather than using checkpoints from one shot as a basis for the next. “Cop圜at enabled us to maximize artist time on areas that required the most attention from us,” Johannes explains.Ĭop圜at was used on two shots in total as part of the project. Ultimately, the use of machine learning on the project was a boon in terms of saving time, so artists could spend it being creative. This shows how simple it is to do tasks which would otherwise need an artist for a considerable amount of time.” After only two hours of training on my laptop, the logo was removed. ![]() Speaking of how specifically Cop圜at was used on Long Live The Prince, he continues: “We had to remove the label of an actor's football jersey and had no compositor available to do the job, so I painted four frames in Photoshop myself and fed them into the node. “Framestore took the entire project on a pro bono basis,” Johannes tells us. Demystifying the dark arts of machine learning is enough to get artists to think about its concepts in a creative way.”Īt just under two minutes long, Long Live the Price serves as an ode to late football prodigy Kiyan Prince, in which he signs for his former football club Queens Park Rangers, going onto wear the squad number ‘30’ to reflect the age he would have been today. “It allows for creative ideas to be driven by artists rather than engineers. “Cop圜at is a simple way to get started,” Johannes explains. Owning many images labeled and ready to be used at a VFX house makes it very interesting to research those topics.” Given Framestore’s ML efforts so far, how does Cop圜at compare? Generative Adversarial Networks (GANs) are constantly on our minds to create new and exciting images. “We have deployed many R&D efforts in machine learning and I’m generating many images with generative art using machine learning. Yet Cop圜at is not Framestore’s first foray into the ML space, as Johannes points out. It’s a concept that we were internally discussing a lot before, and it helped that I‘d spent a lot of time researching it beforehand and that there are super useful YouTube guides available.” “It was super easy to understand it and get going, especially as it was so intuitive. “Cop圜at is a very well-documented Node,” he tells us. Asked about Framestore’s experience using Cop圜at so far, Johannes lends his thought to the ease with which it’s been to pick up and experiment with the tool. Released commercially in March 2021 as part of Nuke 13.0, Cop圜at has spent the past few months settling into pipelines as artists and studios explore its possibilities and potential. We caught up with Johannes to find out a little more about the creative process behind the project, and how machine learning technology in the form of Nuke’s Cop圜at node was deftly used to benefit the production. Under the care of Johannes Saam, Creative Technologist at Framestore, and Karl Wooley, Project Lead, Kiyan’s likeness was sensitively and delicately recreated digitally as part of the campaign’s short film. One such studio was Framestore, who recently used the tool on Long Live the Prince, a ground-breaking anti-knife campaign in which football prodigy Kiyan Price is digitally brought back to life after tragically losing his life in a stabbing attack at the age of 15. Since its launch, Cop圜at has enjoyed rigorous testing by studios large and small. Cop圜at will then train a neural network to replicate the transformation from before to after, and this can be used to apply the effect to the rest of the entire sequence. Should this need to be applied across a sequence, an artist can feed the plug-in with just a few example frames. Included among these is Cop圜at – a plug-in that allows artists to train neural networks to create custom effects for their own image-based tasks.ĭesigned to save artists huge amounts of time, Cop圜at can be used to tackle complex or time-consuming effects such as creating a garbage matte. ![]() ![]() ![]() and updated in the latest release, Nuke 13.1. It was this realization that underpinned the development of Foundry’s machine learning tools, first launched in Nuke 13.0. To overcome these, they need new ways of working supported by the latest technologies and cutting-edge tools. Machine learning continues to make waves across a range of sectors and industries, not least visual effects and animation, both of which can benefit from the time-saving benefits that automation and AI promise.Īnd since schedules are getting tighter whilst projects increase in complexity, studios and artists are met with fresh challenges. ![]()
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