Objaverse-XL brings 10 million 3D objects to generative AI training
Key Points
- Objaverse-XL is a dataset containing over 10 million 3D objects designed to boost 3D computer vision.
- Training the model Zero123 in novel view synthesis with Objaverse-XL showed strong zero-shot generalization abilities.
- The team aims to drive further advancements in 3D computer vision and create applications in augmented and virtual reality.
Researchers unveil Objaverse-XL, a dataset of over 10 million 3D objects, to advance AI development in 3D computer vision and generative AI.
Developments in AI have been accelerated by increased access to large amounts of training data. This is true of generative AI systems for text and images, which have been trained on massive datasets crawled from the web.
One of the next frontiers of AI, 3D computer vision and generative AI for 3D, has lagged behind due to the challenges of acquiring high-quality 3D data.
Objaverse-XL contains 10 million 3D objects
To address this problem, a team of researchers has unveiled Objaverse-XL, a massive collection of over 10 million 3D objects.
Culled from several online sources, including Sketchfab, Thingiverse and Polycam, it is a tenfold expansion of the Objaverse dataset released in April.
At the time, Sketchfab said the data had been collected en masse without its or the artists' knowledge. In February, Sketchfab introduced a NoAI tag to prevent this - too late, as it turned out.
Zero123 is a generative AI model for 3D
Using Objaverse-XL, the researchers have successfully trained a model for novel view synthesis. The resulting model, Zero123-XL, has demonstrated strong zero-shot generalization capabilities across a range of complex modalities, including photorealistic assets, cartoons, drawings, and sketches.
Introducing Objaverse-XL, an open dataset of over 10 million 3D objects!
With it, we train Zero123-XL, a foundation model for 3D, observing incredible 3D generalization abilities: 🧵👇
📝 Paper: https://t.co/2oNakoka7v pic.twitter.com/GJnNbOegab
— Matt Deitke (@mattdeitke) July 11, 2023
According to the researchers, experiments have shown promising scaling trends for 3D vision tasks using Objaverse-XL as data scales from a few thousand to 10 million assets. For this reason, they believe that an even larger dataset containing billions of objects would further enhance the potential capabilities of such AI models.
Objaverse-XL and Zero123 are the result of a cooperation between the Allen AI Institute, Columbia University, UWCSE, Stability AI, LAION and Caltech.
The researchers believe that Objaverse-XL will facilitate advances in AI for 3D by significantly enhancing the performance of state-of-the-art models and enabling applications in areas such as augmented and virtual reality.
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