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However, we contend that such implicit high-dimensional structure modeling approch inadequately represents the local geometric structure of point clouds due to the absence of explicit structural information. Hence, we introduce X-3D, an explicit 3D structure modeling approach. X-3D functions by capturing the explicit local structural information within the input 3D space and employing it to produce dynamic kernels with shared weights for all neighborhood points within the current local region. This modeling approach introduces effective geometric prior and significantly diminishes the disparity between the local structure of the embedding space and the original input point cloud, thereby improving the extraction of local features. Experiments show that our method can be used on a variety of methods and achieves state-of-the-art performance on segmentation, classification, detection tasks with lower extra computational cost, such as \\textbf{90.7\\%} on ScanObjectNN for classification, \\textbf{79.2\\%} on S3DIS 6 fold and \\textbf{74.3\\%} on S3DIS Area 5 for segmentation, \\textbf{76.3\\%} on ScanNetV2 for segmentation and \\textbf{64.5\\%} mAP , \\textbf{46.9\\%} mAP on SUN RGB-D and \\textbf{69.0\\%} mAP , \\textbf{51.1\\%} mAP on ScanNetV2 . Our code is available at \\href{https://github.com/sunshuofeng/X-3D}{https://github.com/sunshuofeng/X-3D}.","url_abs":"https://arxiv.org/abs/2404.15010v1","url_pdf":"https://arxiv.org/pdf/2404.15010v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"x-3d-explicit-3d-structure-modeling-for-point","repo_url":"https://github.com/sunshuofeng/X-3D","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2404.15010","atlas_url":"https://app.syntology.ai/?focus=2404.15010","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.15010"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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