Map-relative pose regression for visual re-localization
Pose regression networks predict the camera pose of a query image relative to a known environment. Within this family of methods, absolute pose regression (APR) has recently shown promising accuracy in the range of a few centimeters in position error. APR networks encode the scene geometry implicitl...
Main Authors: | Chen, S, Cavallari, T, Prisacariu, VA, Brachmann, E |
---|---|
Format: | Internet publication |
Language: | English |
Published: |
2024
|
Similar Items
-
Accelerated coordinate encoding: learning to relocalize in minutes using RGB and poses
by: Brachmann, E, et al.
Published: (2023) -
Accelerated coordinate encoding: learning to relocalize in minutes using RGB and poses
by: Brachmann, E, et al.
Published: (2023) -
Scene coordinate reconstruction: posing of image collections via incremental learning of a relocalizer
by: Brachmann, E, et al.
Published: (2024) -
Matching 2D images in 3D: metric relative pose from metric correspondences
by: Barroso-Laguna, A, et al.
Published: (2024) -
DFNet: enhance absolute pose regression with direct feature matching
by: Chen, S, et al.
Published: (2022)