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AI Technology Makes It Possible to 3D Scan and Edit Real-World Objects



Imagine being able to view a realistic, fully editable 3D model of an object from any angle by simply sweeping your smartphone around it. AI advancements are making this a reality very quickly.

For precisely this purpose, Canadian researchers at Simon Fraser University (SFU) have unveiled new AI technology. Consumers will soon be able to take 3D captures of real-life objects instead of just 2D ones, and edit their shapes and appearance as they like, with the same ease as they can do with regular 2D photos.

Researchers presented Proximity Attention Point Rendering (PAPR), a novel method that converts a collection of 2D images of an object into a cloud of 3D points that depicts the object’s shape and appearance, at the 2023 Conference on Neural Information Processing Systems (NeurIPS) in New Orleans, Louisiana. The paper was published on the arXiv preprint server.

After that, each point has a knob that allows users to manipulate the object: dragging a point modifies its shape, and editing its properties alters its appearance. Afterwards, through a procedure called “rendering,” the 3D point cloud can be viewed from any perspective and converted into a 2D image that accurately depicts the edited object from the perspective from which the image was taken.

Researchers demonstrated how to bring a statue to life using the new AI technology. The technology automatically turned a collection of images of the statue into a 3D point cloud, which is subsequently animated. The final product is a video that shows the statue moving its head side to side while a path is shown around it.

A paradigm shift in the reconstruction of 3D objects from 2D images is primarily being driven by AI and machine learning. According to Dr. Ke Li, senior author of the paper and assistant professor of computer science at Simon Fraser University (SFU), “The outstanding success of machine learning in fields like computer vision and natural language is inspiring researchers to investigate how traditional 3D graphics pipelines can be re-engineered with the same deep learning-based building blocks that were responsible for the recent wave of AI success stories.”

“It turns out that doing so successfully is a lot harder than we anticipated and requires overcoming several technical challenges. What excites me the most is the many possibilities this brings for consumer technology—3D may become as common a medium for visual communication and expression as 2D is today.”

Creating a 3D representation of shapes that is easy and intuitive for users to edit is one of the main challenges in 3D modeling. Neural radiance fields (NeRFs) are one prior method that requires the user to describe what happens to each continuous coordinate, making shape editing difficult. The shape surface may be crushed or shattered after editing, which makes a more modern method called 3D Gaussian splatting (3DGS) unsuitable for shape editing as well.

One of the researchers’ most important insights was realizing that every 3D point in the point cloud could be thought of as a control point in a continuous interpolator rather than as a discrete splat. Subsequently, the shape automatically and intuitively changes when the point is moved. In animated videos, animators use a similar method to define object motion: they specify an object’s position at a few points in time, and an interpolator automatically generates the object’s motion at every point in time.

Nevertheless, it is not easy to define an interpolator mathematically between any random set of 3D points. The scientists developed a machine learning model that uses proximity attention, a novel mechanism, to learn the interpolator in an end-to-end manner.

A spotlight at the NeurIPS conference, an honor given to the top 3.6% of paper submissions, was given to the paper in appreciation of this technological advancement.

The research team is looking forward to the future with excitement. “This opens the way to many applications beyond what we’ve demonstrated,” Dr. Li added. “We are already exploring various ways to leverage PAPR to model moving 3D scenes and the results so far are incredibly promising.”

Ke Li, Yanshu Zhang, Shichong Peng, and Alireza Moazeni are the paper’s authors. Zhang, Peng, and Moazeni are Ph.D. candidates in the School of Computing Science at Simon Fraser University (SFU), and Zhang and Peng are co-first authors.


Biden, Kishida Secure Support from Amazon and Nvidia for $50 Million Joint AI Research Program



As the two countries seek to enhance cooperation around the rapidly advancing technology, President Joe Biden and Japanese Prime Minister Fumio Kishida have enlisted Inc. and Nvidia Corp. to fund a new joint artificial intelligence research program.

A senior US official briefed reporters prior to Wednesday’s official visit at the White House, stating that the $50 million project will be a collaborative effort between Tsukuba University outside of Tokyo and the University of Washington in Seattle. A separate collaborative AI research program between Carnegie Mellon University in Pittsburgh and Tokyo’s Keio University is also being planned by the two nations.

The push for greater research into artificial intelligence comes as the Biden administration is weighing a series of new regulations designed to minimize the risks of AI technology, which has developed as a key focus for tech companies. The White House announced late last month that federal agencies have until the end of the year to determine how they will assess, test, and monitor the impact of government use of AI technology.

In addition to the university-led projects, Microsoft Corp. announced on Tuesday that it would invest $2.9 billion to expand its cloud computing and artificial intelligence infrastructure in Japan. Brad Smith, the president of Microsoft, met with Kishida on Tuesday. The company released a statement announcing its intention to establish a new AI and robotics lab in Japan.

Kishida, the second-largest economy in Asia, urged American business executives to invest more in Japan’s developing technologies on Tuesday.

“Your investments will enable Japan’s economic growth — which will also be capital for more investments from Japan to the US,” Kishida said at a roundtable with business leaders in Washington.

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OnePlus and OPPO Collaborate with Google to Introduce Gemini Models for Enhanced Smartphone AI



As anticipated, original equipment manufacturers, or OEMs, are heavily integrating AI into their products. Google is working with OnePlus, OPPO, and other companies to integrate Gemini models into their smartphones. They intend to introduce the Gemini models on smartphones later this year, becoming the first OEMs to do so. Gemini models will go on sale later in 2024, as announced at the Google Cloud Next 24 event. Gemini models are designed to provide users with an enhanced artificial intelligence (AI) experience on their gadgets.

Customers in China can now create AI content on-the-go with devices like the OnePlus 12 and OPPO Find X7 thanks to OnePlus and OPPO’s Generative AI models.

The AI Eraser tool was recently made available to all OnePlus customers worldwide. This AI-powered tool lets users remove unwanted objects from their photos. For OnePlus and OPPO, AI Eraser is only the beginning.

In the future, the businesses hope to add more AI-powered features like creating original social media content and summarizing news stories and audio.

AndesGPT LLM from OnePlus and OPPO powers AI Eraser. Even though the Samsung Galaxy S24 and Google Pixel 8 series already have this feature, it is still encouraging to see OnePlus and OPPO taking the initiative to include AI capabilities in their products.

OnePlus and OPPO devices will be able to provide customers with a more comprehensive and sophisticated AI experience with the release of the Gemini models. It is important to remember that OnePlus and OPPO already power the Trinity Engine, which makes using phones incredibly smooth, and use AI and computational mathematics to enhance mobile photography.

By 2024, more original equipment manufacturers should have AI capabilities on their products. This is probably going to help Google because OEMs will use Gemini as the foundation upon which to build their features.

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Meta Explores AI-Enabled Search Bar on Instagram



In an attempt to expand the user base for its generative AI-powered products, Meta is moving forward. The business is experimenting with inserting Meta AI into the Instagram search bar for both chat with AI and content discovery, in addition to testing the chatbot Meta AI with users in nations like India on WhatsApp.

When you type a query into the search bar, Meta AI initiates a direct message (DM) exchange in which you can ask questions or respond to pre-programmed prompts. Aravind Srinivas, CEO of Perplexity AI, pointed out that the prompt screen’s design is similar to the startup’s search screen.

Plus, it might make it easier for you to find fresh Instagram content. As demonstrated in a user-posted video on Threads, you can search for Reels related to a particular topic by tapping on a prompt such as “Beautiful Maui sunset Reels.”

Additionally, TechCrunch spoke with a few users who had the ability to instruct Meta AI to look for recommendations for Reels.

By using generative AI to surface new content from networks like Instagram, Meta hopes to go beyond text generation.

With TechCrunch, Meta verified the results of its Instagram AI experiment. But the company didn’t say whether or not it uses generative AI technology for search.

A Meta representative told TechCrunch, “We’re testing a range of our generative AI-powered experiences publicly in a limited capacity. They are under development in varying phases.”

There are a ton of posts available discussing Instagram search quality. It is therefore not surprising that Meta would want to enhance search through the use of generative AI.

Furthermore, Instagram should be easier to find than TikTok, according to Meta. In order to display results from Reddit and TikTok, Google unveiled a new perspectives feature last year. Instagram is developing a feature called “Visibility off Instagram” that could allow posts to appear in search engine results, according to reverse engineer Alessandro Paluzzi, who made this discovery earlier this week on X.

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