Feb. 12, 2024, 5:45 a.m. | Haoyuan Li Yanpeng Zhou Yihan Zeng Hang Xu Xiaodan Liang

cs.CV updates on arXiv.org arxiv.org

3D Shape represented as point cloud has achieve advancements in multimodal pre-training to align image and language descriptions, which is curial to object identification, classification, and retrieval. However, the discrete representations of point cloud lost the object's surface shape information and creates a gap between rendering results and 2D correspondences. To address this problem, we propose GS-CLIP for the first attempt to introduce 3DGS (3D Gaussian Splatting) into multimodal pre-training to enhance 3D representation. GS-CLIP leverages a pre-trained vision-language model …

classification clip cloud cs.cv data gap identification image information language lost multimodal pre-training pretraining rendering retrieval surface training world

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