000108343 001__ 108343
000108343 005__ 20220519113700.0
000108343 0247_ $$2doi$$a10.5220/0010610703300337
000108343 0248_ $$2sideral$$a124899
000108343 037__ $$aART-2021-124899
000108343 041__ $$aeng
000108343 100__ $$0(orcid)0000-0003-4638-4655$$aAlonso, Iñigo$$uUniversidad de Zaragoza
000108343 245__ $$aDomain Adaptation in LiDAR Semantic Segmentation by Aligning Class Distributions
000108343 260__ $$c2021
000108343 5060_ $$aAccess copy available to the general public$$fUnrestricted
000108343 5203_ $$aLiDAR semantic segmentation provides 3D semantic information about the environment, an essential cue for intelligent systems, such as autonomous vehicles, during their decision making processes. Unfortunately, the annotation process for this task is very expensive. To overcome this, it is key to find models that generalize well or adapt to additional domains where labeled data is limited. This work addresses the problem of unsupervised domain adaptation for LiDAR semantic segmentation models. We propose simple but effective strategies to reduce the domain shift by aligning the data distribution on the input space. Besides, we present a learning-based module to align the distribution of the semantic classes of the target domain to the source domain. Our approach achieves new state-of-the-art results on three different public datasets, which showcase adaptation to three different domains.
000108343 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000108343 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000108343 700__ $$0(orcid)0000-0002-6722-5541$$aRiazuelo, Luis$$uUniversidad de Zaragoza
000108343 700__ $$0(orcid)0000-0003-1183-349X$$aMontesano, Luis$$uUniversidad de Zaragoza
000108343 700__ $$0(orcid)0000-0002-7580-9037$$aMurillo, Ana Cristina$$uUniversidad de Zaragoza
000108343 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát.
000108343 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000108343 773__ $$g18 (2021), 330-337$$pProc. (Int. Asia Conf. Inform. Control, Autom., Robot.)$$tProceedings (International Asia Conference on Informatics in Control, Automation, and Robotics)$$x1948-3414
000108343 8564_ $$s4894939$$uhttps://zaguan.unizar.es/record/108343/files/texto_completo.pdf$$yVersión publicada
000108343 8564_ $$s2383956$$uhttps://zaguan.unizar.es/record/108343/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000108343 909CO $$ooai:zaguan.unizar.es:108343$$particulos$$pdriver
000108343 951__ $$a2022-05-19-11:22:23
000108343 980__ $$aARTICLE