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Pi3

yyfz233

$\\pi^3$ reconstructs visual geometry without a fixed reference view, achieving robust, state-of-the-art performance. We introduce $\\pi^3$ (Pi-Cubed), a novel feed-forward neural network that revolutionizes visual geometry reconstruction by **eliminating the need for a fixed reference view**. Traditional methods, which rely on a designated reference frame, are often prone to instability and failure if the reference is suboptimal. In contrast, $\\pi^3$ employs a fully **permutation-equivariant** architecture. This allows it to directly predict affine-invariant camera poses and scale-invariant local point maps from an unordered set of images, breaking free from the constraints of a reference frame. This design makes our model inherently **robust to input ordering** and **highly scalable**.

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Pi3X

yyfz233

This repository contains the weights for **Pi3X**, an enhanced version of the $\pi^3$ model introduced in the paper $\pi^3$: Permutation-Equivariant Visual Geometry Learning. $\pi^3$ is a feed-forward neural network for visual geometry reconstruction that eliminates the need for a fixed reference view. It employs a fully permutation-equivariant architecture to predict affine-invariant camera poses and scale-invariant local point maps from an unordered set of images, making it robust to input ordering and achieving state-of-the-art performance. - **Project Page:** yyfz.github.io/pi3/ - **GitHub Repository:** github.com/yyfz/Pi3 - **Demo:** Hugging Face Space

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Pi3

Pi3X

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