Neural refinement for absolute pose regression with feature synthesis
Absolute Pose Regression (APR) methods use deep neural networks to directly regress camera poses from RGB images. Despite their advantages in inference speed and simplicity, these methods still fall short of the accuracy achieved by geometry-based techniques. To address this issue, we propose a new...
| Main Authors: | , , , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
IEEE
2024
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