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Existing Transformer-based models for point cloud analysis suffer from quadratic complexity, leading to compromised point cloud resolution and information loss.
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Point Transformer. In Int. Conf. Comput. Vis. (ICCV) . IEEE, 16239–16248
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Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space
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Self-Positioning Point-Based Transformer for Point Cloud Understanding. In IEEE/CVF Conf. Comput. Vis. Pattern Recog. (CVPR) . 21814–21823
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Point-LGMask: Local and Global Contexts Embedding for Point Cloud Pre-training with Multi-Ratio Masking
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Point2Vec for Self-Supervised Representation Learning on Point Clouds
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Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models. In Int. Conf. Comput. Vis. (ICCV) . 14161–14170
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PointGPT: Auto-regressively Generative Pre-training from Point Clouds
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PointMamba: A Simple State Space Model for Point Cloud Analysis
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patchDPCC: A Patchwise Deep Compression Framework for Dynamic Point Clouds. In AAAI Conf. Artif. Intell. (AAAI) , Vol. 38. 4406–4414
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ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
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Point Could Mamba: Point Cloud Learning via State Space Model
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Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis. In IEEE/CVF Conf. Comput. Vis. Pattern Recog. (CVPR) . 14707–14717
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Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
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