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This paper proposes a generalizable, end-to-end deep learning-based method for relative pose regression between two images.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
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Dsac-differentiable ransac for camera localization
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Camera relocalization by computing pairwise relative poses using convolutional neural network
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Visual camera re-localization from rgb and rgb-d images using dsac
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Emerging properties in self-supervised vision transformers
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COTR: Correspondence transformer for matching across images
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Vision transformers for dense prediction
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Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction
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Learning accurate dense correspondences and when to trust them
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Visual camera re-localization using graph neural networks and relative pose supervision
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Learning to localize in new environments from synthetic training data
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Deep vit features as dense visual descriptors
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The 8-point algorithm as an inductive bias for relative pose prediction by ViTs
Chris Rockwell, Justin Johnson, and David F Fouhey · 2022
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Splicing vit features for semantic appearance transfer
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