MultiScan: Scalable RGBD scanning for 3D environments with articulated objects
Yongsen Mao, Yiming Zhang, Hanxiao Jiang, Angel X. Chang, Manolis Savva
摘要
We introduce MultiScan, a scalable RGBD dataset construction pipeline leveraging commodity mobile devices to scan indoor scenes with articulated objects and web-based semantic annotation interfaces to efficiently annotate object and part semantics and part mobility parameters. We use this pipeline to collect 273 scans of 117 indoor scenes containing 10957 objects and 5129 parts. The resulting MultiScan dataset provides RGBD streams with per-frame camera poses, textured 3D surface meshes, richly annotated part-level and object-level semantic labels, and part mobility parameters. We validate our dataset on instance segmentation and part mobility estimation tasks and benchmark methods for these tasks from prior work. Our experiments show that part segmentation and mobility estimation in real 3D scenes remain challenging despite recent progress in 3D object segmentation.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper31
- GPT4Scene: Understand 3D Scenes from Videos with Vision-Language ModelsZhangyang Qi, Zhixiong Zhang, Ye Fang, Jiaqi Wang 等ICLR 2026 · 被引用 121 次
- PARIS: Part-level Reconstruction and Motion Analysis for Articulated ObjectsJiayi Liu, Ali Mahdavi-Amiri, Manolis SavvaICCV 2023 · 被引用 103 次
- SpatialLM: Training Large Language Models for Structured Indoor ModelingYongsen Mao, Junhao Zhong, Chuan Fang, Jia Zheng 等NeurIPS 2025 · 被引用 89 次
- InternSpatial: A Comprehensive Dataset for Spatial Reasoning in Vision-Language ModelsNianchen Deng, Lixin Gu, Shenglong Ye, Yinan He 等ICLR 2026 · 被引用 32 次
- Spatial Understanding from Videos: Structured Prompts Meet Simulation DataHaoyu Zhang, Meng Liu, Zaijing Li, Haokun Wen 等NeurIPS 2025 · 被引用 31 次
它引用的顶会 Paper14
- 3D Scene Graph: A Structure for Unified Semantics, 3D Space, and CameraIro Armeni, Zhi-Yang He, Amir Zamir, JunYoung Gwak 等ICCV 2019 · 被引用 474 次
- RIO: 3D Object Instance Re-Localization in Changing Indoor EnvironmentsJohanna Wald, Armen Avetisyan, Nassir Navab, Federico Tombari 等ICCV 2019 · 被引用 233 次
- Hierarchical Aggregation for 3D Instance SegmentationShaoyu Chen, Jiemin Fang, Qian Zhang, Wenyu Liu 等ICCV 2021 · 被引用 211 次
- Instance Segmentation in 3D Scenes using Semantic Superpoint Tree NetworksZhihao Liang, Zhihao Li, Songcen Xu, Mingkui Tan 等ICCV 2021 · 被引用 170 次
- A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape RepresentationJiteng Mu, Weichao Qiu, Adam Kortylewski, Alan L. Yuille 等ICCV 2021 · 被引用 138 次
相关 Paper
- ScanNet++: A High-Fidelity Dataset of 3D Indoor ScenesChandan Yeshwanth, Yueh-Cheng Liu, Matthias Nießner, Angela DaiICCV 2023 · 被引用 659 次
- MobileBrick: Building LEGO for 3D Reconstruction on Mobile DevicesKejie Li, Jia-Wang Bian, Robert Castle, Philip H. S. Torr 等CVPR 2023
- Semi-Weakly Supervised Object Kinematic Motion PredictionGengxin Liu, Qian Sun, Haibin Huang, Chongyang Ma 等CVPR 2023
- HOI4D: A 4D Egocentric Dataset for Category-Level Human-Object InteractionYunze Liu, Yun Liu, Che Jiang, Kangbo Lyu 等CVPR 2022 · 被引用 126 次
- CAD-Estate: Large-scale CAD Model Annotation in RGB VideosKevis-Kokitsi Maninis, Stefan Popov, Matthias Nießner, Vittorio FerrariICCV 2023 · 被引用 14 次
