CLIP<sup>2</sup>: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data-Reference-Cited by-同舟云学术

CLIP²: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data

Published:2023-06 Issue: Volume: Page:
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Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Zeng Yihan¹,Jiang Chenhan²,Mao Jiageng³,Han Jianhua¹,Ye Chaoqiang¹,Huang Qingqiu¹,Yeung Dit-Yan²,Yang Zhen¹,Liang Xiaodan⁴,Xu Hang¹

Affiliation:

1. Huawei Noah's Ark Lab

2. Hong Kong University of Science and Technology

3. The Chinese University of Hong Kong

4. Sun Yat-san University

Publisher

IEEE

Link

Reference44 articles.

1. Clip2point: Transfer clip to point cloud classification with image-depth pre-training;huang;ArXiv Preprint,2022

3. Semantic abstraction: Open-world 3d scene understanding from 2d vision-language models;ha;CoRL,2022

4. Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data;angelina uy;ICCV,2019

5. Align before fuse: Vision and language representation learning with momentum distillation;li;NeurIPS,2021

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