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The field of learned image compression has been facing rapid development and research engagement. In this thesis, we seek to make an addition to the field by extending a state-of-the-art learned image compression architecture, called LIC-TCM, by incorporating a depth map as a second complementary modality to further enhance the image compression. Furthermore, we explore the inverse, meaning we pri
