A pair of hands holds a digital camera. "NUCA" is written in the hood above the lens and a black grip is on the right hand side of the device (left side of image). The camera body is off-white 3D printed plastic. The background is a pastel yellow.

AI Camera Only Takes Nudes

One of the cringier aspects of AI as we know it today has been the proliferation of deepfake technology to make nude photos of anyone you want. What if you took away the abstraction and put the faker and subject in the same space? That’s the question the NUCA camera was designed to explore. [via 404 Media]

[Mathias Vef] and [Benedikt Groß] designed the NUCA camera “with the intention of critiquing the current trajectory of AI image generation.” The camera itself is a fairly unassuming device, a 3D-printed digital camera (19.5 × 6 × 1.5 cm) with a 37 mm lens. When the camera shutter button is pressed, a nude image is generated of the subject.

The final image is generated using a mixture of the picture taken of the subject, pose data, and facial landmarks. The photo is run through a classifier which identifies features such as age, gender, body type, etc. and then uses those to generate a text prompt for Stable Diffusion. The original face of the subject is then stitched onto the nude image and aligned with the estimated pose. Many of the sample images on the project’s website show the bias toward certain beauty ideals from AI datasets.

Looking for more ways to use AI with cameras? How about this one that uses GPS to imagine a scene instead. Prefer to keep AI out of your endeavors to invade personal space? How about building your own TSA body scanner?


AI Image Generation Meets Virtual Dress Up

Image generators have really taken off thanks to machine learning, and all kinds of new ideas have been turned on in people’s heads as a result. OOTDiffusion is one such project, its job being to allow virtual try-ons of clothing by combining a picture of a person and an item of clothing, and doing so in a coherent way.

A model sporting a 2021 Remoticon shirt.

When it comes to AI image generators, maintaining consistency of a particular subject in a picture while changing or combining other parts of the image isn’t a trivial task. (If you’re unfamiliar with the basics of how diffusion-type AI image generators work, we have you covered.)

Virtual try-on of clothing is not a new idea, but it’s also far from being a completely solved problem. It’s easy to feed a system high-quality images of people and clothing and ask it to combine them, but the outputs rarely emerge with all their limbs intact, figuratively speaking.

OOTDiffusion addresses the two big challenges in this area: making sure the outputs look natural and realistic, and preserving as much of the garment’s appearance and qualities as possible in the process.

It seems to to a very good job, and you can try it for yourself in the online demo. Check out the research paper for more details, and the GitHub repository provides all the code if you’d like to get a little more hands-on.

How Do You Prove An AI Didn’t Make Your Art?

In the world of digital art, distinguishing between AI-generated and human-made creations has become a significant challenge. Almost overnight, tool sets for generating AI artworks became commonly available to the public, and suddenly, every digital art competition had to contend with potential submissions. Some have welcomed AI, while others demand competitors create artworks by their own hand and no other.

The problem facing artists and judges alike is just how to determine whether an artwork was created by a human or an AI. So what can be done?

Continue reading “How Do You Prove An AI Didn’t Make Your Art?”

AI Camera Imagines A Photo Of What You Point It At

These days, every phone has a camera, and few of us are ever without one. [Bjørn Karmann] has built an altogether not-camera, though, in the form of the Paragraphica, powered by artificial intelligence.

The Paragraphica doesn’t actually take photographs at all. Instead, it uses GPS to determine the user’s current position. It then feeds the address, time of day, weather, and temperature into a paragraph which serves as a prompt for an AI image generator. It also uses data gathered from various APIs to determine points of interest in the immediate area, and feeds those into the prompt as well. It then generates an artificial image that is intended to bear some resemblance to the prompt, and ideally, the real-world scene. In place of a lens, it bears a 3D printed structure inspired by the star-nosed mole, which feels its way around in lieu of using its eyes.

Three dials on the Paragraphica control its action. The first dial controls the radius of the area which the prompt will gather data about; it’s akin to setting the focal length of the lens. The second dial provides a noise seed value for the AI image generator, and the third dial controls how closely the AI sticks to the generated textual prompt.

The results are impressive, if completely false and generated from scratch. The Paragraphica generates semi-believable photos of a crowded alley, a public park, and a laneway full of parked cars. It’s akin to telling a friend where you are and what you’re seeing over the phone, and having them paint a picture based on that description.

Through their unique abilities and stolen data sets, AI image generators are proving controversial to say the least. As all good art does, Paragraphica explores this and raises new questions of its own.