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In recent years, 3D understanding has turned to 2D vision-language pre-trained models to overcome data scarcity challenges.
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CLIP goes 3D: Leveraging Prompt Tuning for Language Grounded 3D Recognition
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RefCLIP: A Universal Teacher for Weakly Supervised Referring Expression Comprehension. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 2681–2690
Lei Jin, Gen Luo, Yiyi Zhou, Xiaoshuai Sun, Guannan Jiang, Annan Shu, and Rongrong Ji. 2023 · 2023
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X-Mesh: Towards Fast and Accurate Text-driven 3D Stylization via Dynamic Textual Guidance
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Towards real-time panoptic narrative grounding by an end-to-end grounding network
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Unsupervised Point Cloud Representation Learning with Deep Neural Networks: A Survey
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CLIP-FO3D: Learning Free Open-world 3D Scene Representations from 2D Dense CLIP
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Generating Visual Spatial Description via Holistic 3D Scene Understanding. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 7960–7977
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