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The developers at MeshAnything have just released new code that offers an important improvement in how the surface of 3D objects can be encoded. What the new method does is build out the shape by always seeking to find and encode an adjacent face that shares an edge, which requires only about half as many tokens to represent the same information by other methods, resulting in a four-fold reduction in the memory requirement to achieve the same task, which enabled MeshAnything to double the maximum number of faces it can handle on a single object to 1600, as compared to 800 for current methods.
This video starts by comparing the new method with the current one. After that, we generate a 3D object from a text prompt on the Rodin website (a pink hippopotamus ballerina character with white tutu), and we check it on the Sketchfab website. Then we run the code that was provided by MeshAnything on GitHub, and we check the output on Sketchfab, comparing before and after side-by-side. The results confirm the final words of the paper, which state that “the accuracy of MeshAnything V2 is still insufficient for industrial applications. More efforts are needed.” Nonetheless, this new computational approach is elegant, and the video concludes with a prediction that we’ll likely see improvements that build on the foundations laid by MeshAnything V2.
Google DeepMind has just achieved a new level of robotic skill – the ability to compete and win at table tennis, a game that requires years of training for people […]
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