Issue link: http://digital.copcomm.com/i/1399888
j u ly • a u g u s t • s e p t e m b e r 2 0 2 1 c g w 9 instance, the way the blood flow changes in the lips as you're talking, which can make it feel real or not." This is where DHG's hybrid approach comes into play in many of its productions, as the group uses a 3D version of a character and then on top of it, they employ a new type of neural network approach whereby the machine learning model tweaks the CG model of the character to be more realistic. In fact, the DHG is employing this hybrid approach to the ongoing development of Douglas, a realistic real-time autonomous digital human — the next step in the evolu- tion of digital humans (see "Douglas," page 8). Creating a really high resolution, realistic, pre-rendered character that artists can control is vastly different to having a digital character infused with complex AI that can interact with people in real time. And while portions of the creation process between the two types are very similar, the outcomes are very different. Both processes start out with build- ing the full-3D version of the character's face (with face shapes, pore structures, and textures). For its digital characters, the DHG uses a combination of custom soware and commercial products, such as Autodesk's Maya and Foundry's Mari and Nuke, in addition to machine learn- ing framework tools, such as PyTorch, an open-source machine learning library, for functions such as speech recognition. "We're feeding in much of the same data, even the way the wardrobe is modeled; just the rendering engine is different," says Hendler, emphasizing that a large amount of artistry goes into the entire process. Traditionally for a film asset, Digital Domain employs an offline renderer like Chaos' V-Ray; for an autonomous char- acter rendered in real time, the group uses Unreal. While the real-time aspect is achieved through the Unreal Engine, the output of the autonomous character, unlike a character in a video game, is not through Unreal. Unreal is an intermediate step, says Roble. "Then we send that through our neural rendering, which redoes some of the imagery," he explains. So, while the digital character goes through an extra layer of reality, backgrounds, for instance, are purely output from Unreal. According to Roble, as Douglas pro- gresses, DHG is moving away from the 3D creation model and moving more toward using neural rendering for that aspect. The Digital Human League Another group that delves deep into the creation of realistic digital humans is Chaos Labs, an applied science start-up founded in August 2014 that acts as a bridge of sorts between artists and devel- opers by looking at where the industry is headed and what innovative technology artists will need to get there. This encom- passes many advanced developments, including digital humans. Chaos Labs has been doing a lot of work in this particular area, specifically related to shaders (Chaos is the developer of V-Ray, one of the industry's top shading/rendering soware). "And the best way we could go about exploring [the creation of realistic digital humans] was by creating or working with a really, really good dataset. That is what inspired the Wikihuman Project," says Chris Nichols, director of Chaos Labs. The Wikihuman Project was established and dedicated to the study, understanding, and sharing of knowledge pertaining to digital humans. Run by the Digital Human League (DHL), a panel of academic and in- dustry experts, the site was open to anyone interested in crossing the uncanny valley. "People have been battling the uncanny valley for far longer than computer graphics has been around. They've been doing this for hundreds and hundreds of years. And some would even say that the Mona Lisa is a perfect example of the uncanny valley because she doesn't quite look right," says Nichols. As Nichols points out, the overall goal of DHL was to give people a good starting point for their work, rather than to advance specif- ics in terms of digital humans. "Back in the day, it always felt like we were starting from scratch with a dataset," he says. "We needed a baseline, and that is what we were trying to accomplish with the Wikihuman Project." Both Wikihuman and DHL have since dis- banded aer achieving their goals, releasing Digital Emily 2, a free, high-res 3D scan of a fe- male human head, establishing a baseline for other artists to use and learn from; it helped get Digital Mike Seymour off the ground. Since this time, there have been large advancements of digital humans for film, ©Ian Springs