Bi-directional attention based RGB-D fusion for category-level object pose and shape estimation
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17626-6.pdf
Reference64 articles.
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2. Brachmann E, Krull A, Michel F, et al (2014) Learning 6d object pose estimation using 3d object coordinates. In: Eur Conf Comput Vis, pp 536–551. https://doi.org/10.1007/978-3-319-10605-2_35
3. Chen CFR, Fan Q, Panda R (2021a) Crossvit: Cross-attention multi-scale vision transformer for image classification. In: IEEE Int Conf Comput Vis, Montreal, QC, Canada, pp 357–366. https://doi.org/10.1109/ICCV48922.2021.00041
4. Chen D, Li J, Wang Z, et al (2020) Learning canonical shape space for category-level 6d object pose and size estimation. In: IEEE Conf Comput Vis Pattern Recognit, Seattle, WA, USA, pp 11973–11982. https://doi.org/10.1109/CVPR42600.2020.01199
5. Chen K, Dou Q (2021) Sgpa: Structure-guided prior adaptation for category-level 6d object pose estimation. In: IEEE Int Conf Comput Vis, Montreal, QC, Canada, pp 2773–2782. https://doi.org/10.1109/ICCV48922.2021.00277
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