Current regression-based methods for pose estimation are trained and evaluated scene-wise… They depend on the coordinate frame of the training dataset and show a low generalization across scenes and datasets . We develop a deep adaptation network for learning scene-invariant image representations and use adversarial learning to generate such representations for model transfer . We evaluate our network on two public datasets, Cambridge Landmarks and 7Scene, demonstrate its superiority over several baselines and compare to the state-of-the-art methods . We use the adaptability theory to validate the existence of scene-Invariant representation of images in two given scenes . We enrich the network with self-supervised learning and use the Adaptability Theory to . validate the¬†adaptability theory¬†to validate the . existence of the adaptable theory to validated the adaptibility theory . We demonstrate our network

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Keywords : theory - network - scene - adaptability - validate -

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