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UFO Depth: Unsupervised learning with flow-based odometry optimization for metric depth estimation., , , , , , и . ICRA, стр. 6526-6532. IEEE, (2022)Mining for meaning: from vision to language through multiple networks consensus., , , и . BMVC, стр. 275. BMVA Press, (2018)Self-supervised Hypergraphs for Learning Multiple World Interpretations., , , , , , , и . ICCV (Workshops), стр. 983-992. IEEE, (2023)Discovering Dynamic Salient Regions for Spatio-Temporal Graph Neural Networks., , и . NeurIPS, стр. 7111-7125. (2021)Unsupervised Learning of Object Features from Video Sequences., и . CVPR (1), стр. 1142-1149. IEEE Computer Society, (2005)A Spectral Technique for Correspondence Problems Using Pairwise Constraints., и . ICCV, стр. 1482-1489. IEEE Computer Society, (2005)Discovering Texture Regularity as a Higher-Order Correspondence Problem., , , и . ECCV (2), том 3952 из Lecture Notes in Computer Science, стр. 522-535. Springer, (2006)Towards a Human-Centered Approach for VRET Systems: Case Study for Acrophobia., , , , , и . ISD, ISEN Yncréa Méditerranée / Association for Information Systems, (2019)Automatic Adaptation of Exposure Intensity in VR Acrophobia Therapy, based on Deep Neural Networks., , , , и . ECIS, (2019)GEST: the Graph of Events in Space and Time as a Common Representation between Vision and Language., , , и . CoRR, (2023)