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...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2023
|
| Subjects: | |
| 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 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Singapore Management University |
| Language: | English |