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Existing panoramic depth estimation methods based on convolutional neural networks (CNNs) focus on removing panoramic distortions, failing to perceive panoramic structures efficiently due to the fixed receptive field in CNNs.
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2022
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Yun, I., Lee, H.J., Rhee, C.E.: Improving 360 monocular depth estimation via non-local dense prediction transformer and joint supervised and self-supervised learning. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 36, pp. 3224–3233 (2022)
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