Invariant training 2D-3D joint hard samples for few-shot point cloud recognition
We tackle the data scarcity challenge in few-shot point cloud recognition of 3D objects by using a joint prediction from a conventional 3D model and a well-pretrained 2D model. Surprisingly, such an ensemble, though seems trivial, has hardly been shown effective in recent 2D-3D models. We find out t...
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Main Authors: | , , , , , |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
2023
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Online Access: | https://ink.library.smu.edu.sg/sis_research/8389 https://ink.library.smu.edu.sg/context/sis_research/article/9392/viewcontent/Yi_Invariant_Training_2D_3D_Joint_Hard_Samples_for_Few_Shot_Point_Cloud_ICCV_2023_paper__1_.pdf |
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Institution: | Singapore Management University |
Language: | English |
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