The 8-Point Algorithm as an Inductive Bias for Relative Pose Prediction by ViTs
Abstract
A modified Vision Transformer achieves competitive performance in relative pose estimation with simple modifications and minimal data.
We present a simple baseline for directly estimating the relative pose (rotation and translation, including scale) between two images. Deep methods have recently shown strong progress but often require complex or multi-stage architectures. We show that a handful of modifications can be applied to a Vision Transformer (ViT) to bring its computations close to the Eight-Point Algorithm. This inductive bias enables a simple method to be competitive in multiple settings, often substantially improving over the state of the art with strong performance gains in limited data regimes.
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