HyperPose: Hypernetwork-Infused Camera Pose Localization and an Extended Cambridge Landmarks Dataset

Understand

In this work, we propose HyperPose, which utilizes hyper-networks in absolute camera pose regressors.

• The inherent appearance variations in natural scenes, attributable to environmental conditions, perspective, and lighting, induce a significant domain disparity between the training and test datasets.
• This disparity degrades the precision of contemporary localization networks.
• To mitigate this, we advocate for incorporating hypernetworks into single-scene and multiscene camera pose regression models.