Paparazzo: Active Mapping of Moving 3D Objects
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Abstract (arXiv)
Current 3D mapping pipelines generally assume static environments, which limits their ability to accurately capture and reconstruct moving objects. To address this limitation, we introduce the novel task of active mapping of moving objects, in which a mapping agent must plan its trajectory while compensating for the object's motion. Our approach, Paparazzo, provides a learning-free solution that robustly predicts the target's trajectory and identifies the most informative viewpoints from which to observe it, to plan its own path. We also contribute a comprehensive benchmark designed for this new task. Through extensive experiments, we show that Paparazzo significantly improves 3D reconstruction completeness and accuracy compared to several strong baselines, marking an important step toward dynamic scene understanding. Project page: https://davidea97.github.io/paparazzo-page/
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 32 references that are in the map. First posted on arXiv 21 Apr 2026.
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17 of 32 references.
References · 17
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
- 2017Matterport3D: Learning from RGB-D Data in Indoor Environmentscited by 1,376
- 2018Gibson Env: Real-World Perception for Embodied Agentscited by 481
- 2023SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAMcited by 388
- 2023Habitat 3.0: A Co-Habitat for Humans, Avatars and Robotscited by 228
- 2023Segment Anything Meets Point Trackingcited by 81
- 2021NeuralDiff: Segmenting 3D objects that move in egocentric videoscited by 57
- 2024ActiveGS: Active Scene Reconstruction Using Gaussian Splattingcited by 35
- 20173D Object Reconstruction from Hand-Object Interactionscited by 31
- 2023Active Neural Mappingcited by 31
- 2024NARUTO: Neural Active Reconstruction from Uncertain Target Observationscited by 28
- 2022In-Hand 3D Object Scanning from an RGB Sequencecited by 27
5 more
- 2021DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstrationcited by 20
- 2023MACARONS: Mapping And Coverage Anticipation with RGB Online Self-Supervisioncited by 19
- 2024KISS-Matcher: Fast and Robust Point Cloud Registration Revisitedcited by 16
- 2025NextBestPath: Efficient 3D Mapping of Unseen Environmentscited by 13
- 20246DOPE-GS: Online 6D Object Pose Estimation using Gaussian Splattingcited by 11
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