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The 8-Point Algorithm as an Inductive Bias for Relative Pose Prediction by ViTs

About

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.

Chris Rockwell, Justin Johnson, David F. Fouhey• 2022

Related benchmarks

TaskDatasetResultRank
Rotation EstimationSUN360 Large Overlap
Geodesic Error (Mean)22.33
13
Pose EstimationACID Small
Rotation Avg Error (°)8.466
7
Pose EstimationACID Large
Rotation Avg Error (°)2.28
7
Pose EstimationACID (Avg)
Rotation Avg Error (°)4.568
7
Pose EstimationACID Medium
Rotation Avg Error (°)4.325
7
Rotation EstimationsELP Small overlap (test)
MGE51.3
7
Pose EstimationRealEstate-10K (Small)
Rotation Average Error (Avg)12.604
7
Pose EstimationRealEstate-10K Medium
Rotation Average Error (Degrees)12.168
7
Pose EstimationRealEstate-10K Large
Rotation Avg Error (°)12.771
7
Pose EstimationRealEstate-10K (Avg)
Rotation Avg Error12.585
7
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