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VisDA-2021 Competition: Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data., , , , , , , , , and 1 other author(s). NeurIPS (Competition and Demos), volume 176 of Proceedings of Machine Learning Research, page 66-79. PMLR, (2021)VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting., , , , , , , , , and 9 other author(s). NeurIPS (Competition and Demos), volume 220 of Proceedings of Machine Learning Research, page 104-118. PMLR, (2021)VisDA-2021 Competition Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data., , , , , , , and . CoRR, (2021)Effectively Leveraging Attributes for Visual Similarity., , , , , and . ICCV, page 995-1004. IEEE, (2021)Faster Algorithms for Weighted Recursive State Machines., , , and . ESOP, volume 10201 of Lecture Notes in Computer Science, page 287-313. Springer, (2017)How Transferable are Video Representations Based on Synthetic Data?, , , , , , , , , and . NeurIPS, (2022)Fine-grained Few-shot Recognition by Deep Object Parsing., , , and . BMVC, page 330-331. BMVA Press, (2023)Fine-grained Few-shot Recognition by Deep Object Parsing., , , and . CoRR, (2022)Incremental Object Learning From Contiguous Views., , , , , , , and . CVPR, page 8777-8786. Computer Vision Foundation / IEEE, (2019)Low Dimensional Visual Attributes: An Interpretable Image Encoding., , , and . ICPR Workshops (3), volume 12663 of Lecture Notes in Computer Science, page 90-102. Springer, (2020)