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The acquisition of dense ground-truth annotations for depth completion settings can be difficult and, at the same time, a significant domain gap between real LiDAR measurements and synthetic data has prevented from successful training of models in virtual settings. We propose a domain adaptation approach for sparse-to-dense depth completion that is trained from synthetic data, without annotations in the real domain or additional sensors. Our approach simulates the real sensor noise in an RGB\u00a0+\u00a0LiDAR set-up, and consists of three modules: simulating the real LiDAR input in the synthetic domain via projections, filtering the real noisy LiDAR for supervision and adapting the synthetic RGB image using a CycleGAN approach. We extensively evaluate these modules in the KITTI depth completion benchmark.\n<\/jats:p>","DOI":"10.1007\/s11263-022-01726-1","type":"journal-article","created":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T11:02:56Z","timestamp":1671188576000},"page":"796-812","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Data"],"prefix":"10.1007","volume":"131","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3984-5126","authenticated-orcid":false,"given":"Adrian","family":"Lopez-Rodriguez","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0620-5774","authenticated-orcid":false,"given":"Benjamin","family":"Busam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0726-9187","authenticated-orcid":false,"given":"Krystian","family":"Mikolajczyk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,12,16]]},"reference":[{"key":"1726_CR1","unstructured":"Abramov, A., Bayer, C., & Heller, C. 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