Aug. 26, 2022, 1:13 a.m. | Guocheng Qian, Xingdi Zhang, Abdullah Hamdi, Bernard Ghanem

cs.CV updates on arXiv.org arxiv.org

Pure Transformer models have achieved impressive success in natural language
processing and computer vision. However, one limitation with Transformers is
their need for large training data. In the realm of 3D point clouds, the
availability of large datasets is a challenge, which exacerbates the issue of
training Transformers for 3D tasks. In this work, we empirically study and
investigate the effect of utilizing knowledge from a large number of images for
point cloud understanding. We formulate a pipeline dubbed \textit{Pix4Point} …

3d arxiv cloud cv image transformers understanding

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