AI ML DL

AI ML DL

One Landmark Estimator to Rule Them All

Putting dots on faces has been a staple of computer vision and visual effects processes for decades. It may seem old hat in the age of transformers and Stable Diffusion, but, along with CGI-aided neural rendering processes, it offers a level of control that is missing in dazzling new generative AI systems – and a new system from China proposes a landmark method that could cover all species, instead of needing individual systems for faces, hands, animals and other sub-categories.

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AI ML DL

Better GAN Disentanglement Could Facilitate Better Synthetic Data

If you’re old, you wear glasses. If you’re smiling, you’re probably a woman. These and many other assumptions and biases in datasets lead to generative systems that can produce biased images with unwanted elements. But new research from Canada and the US offers a way to disentangle these ‘spurious associations’, and may help to develop better systems to produce synthetic data for VFX and other purposes.

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AI ML DL

Uncovering a Body With AI

Neural synthesis has a harder time depicting a person sitting at a desk than CGI does, because CGI has legs ‘waiting in the wings’ if they’re needed, whereas the neural pipeline only knows about what it can see. For this reason, new research is offering a better method of handling occlusion for AI-generated humans, albeit in an uneasy partnership with CGI itself.

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AI ML DL

Improving Facial Expression Recognition by Studying Context and Environment

Understanding what facial expressions mean is going to be essential in neural facial synthesis in the coming years. But in many cases, it’s extremely difficult to correctly guess an emotion unless you can see more of the context than just the face (one example being ’embarrassment’, which of necessity cannot be felt or studied without understanding the context). Now, researchers from Canada are proposing a more intelligent annotation pipeline, using Large Language Models such as GPT3, in order to bring more intelligence to Facial Expression Recognition (FER).

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AI ML DL

Controlling Age With AI

Films such as ‘Here’ and ‘Indiana Jones and the Dial of Destiny’ are using advanced machine learning technologies to age and de-age characters. But it’s still a pretty ‘manual’ and painfully laborious process. Now, new research offers a potential pipeline that could shave off or add years to actors in a more systematic way, with the use of Stable Diffusion.

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AI ML DL

Solving the ‘Profile View Famine’ With Generative Adversarial Networks

It’s hard to guess what people look like from the side if you only have frontal views of their face; and the chronic lack of profile views in popular datasets makes this a stubborn data problem that’s standing in the way of 360-degree facial synthesis. Now, researchers from Korea are offering a method that might alleviate this traditional roadblock.

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AI ML DL

Repairing Demographic Imbalance in Face Datasets With StyleGAN3

New research from France and Switzerland uses Generative Adversarial Networks (GANs) to create extra examples of races and genders that are under-represented in historical face datasets, in an effort to offset controversies such as the tendency for facial recognition systems to fail to recognize (or to over-recognize) particular types of people.

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AI ML DL

Stable Diffusion Deepfakes and Stylizations With a Single Image

Getting your face into Stable Diffusion has been a relatively complicated affair since the text-to-image system launched in August of 2022 – but a new offering from China and Singapore proposes a method of embedding your own image into Stable Diffusion with only a single photo, instead of needing to train a model every time.

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AI ML DL

Replacing LoRA With a Generic Style Adapter in Stable Diffusion

For creating personalized Stable Diffusion art, Low Rank Adaption (LoRA) models are all the rage this year. But a new academic offering from China is proposing a system that could bake such elegant functionality directly into Stable Diffusion, without the need to curate data and train models.

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AI ML DL

Detecting Cheapfakes With Deepfakes

You don’t need a powerful GPU to deceive the public – just a mischievous turn of phrase, applied to photos or videos that don’t really support the caption. Now, researchers from Norway are using generative systems such as Stable Diffusion and DALL-E 2 to help root out this kind of ‘cheapfake’ or ‘shallowfake’

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