ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting Residuals
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Abstract (arXiv)
Mapping and localization are essential capabilities of robotic systems. Although the majority of mapping systems focus on static environments, the deployment in real-world situations requires them to handle dynamic objects. In this paper, we propose an approach for an RGB-D sensor that is able to consistently map scenes containing multiple dynamic elements. For localization and mapping, we employ an efficient direct tracking on the truncated signed distance function (TSDF) and leverage color information encoded in the TSDF to estimate the pose of the sensor. The TSDF is efficiently represented using voxel hashing, with most computations parallelized on a GPU. For detecting dynamics, we exploit the residuals obtained after an initial registration, together with the explicit modeling of free space in the model. We evaluate our approach on existing datasets, and provide a new dataset showing highly dynamic scenes. These experiments show that our approach often surpass other state-of-the-art dense SLAM methods. We make available our dataset with the ground truth for both the trajectory of the RGB-D sensor obtained by a motion capture system and the model of the static environment using a high-precision terrestrial laser scanner. Finally, we release our approach as open source code.
Key facts. Cited by 180 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 May 2019.
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Citing papers per year: 2021: 2; 2022: 6; 2023: 4; 2024: 17; 2025: 62; 2026: 89.
180 papers.
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- 2025π3: Permutation-Equivariant Visual Geometry Learningcited by 292
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- 2025Video Depth Anything: Consistent Depth Estimation for Super-Long Videoscited by 202
- 2025Streaming 4D Visual Geometry Transformercited by 147
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- 2026RegVGGT: Sustainable Visual Geometry Grounding for Streaming via Regulated Memory20 Sep 2026
- 2026Info3R: Information-Adaptive Test-Time Training for 3D Reconstruction18 Sep 2026
- 2026Think Locally, Refine Globally for Memory-Efficient 3D Reconstruction18 Sep 2026
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- 2026SCOUT-SLAM: Structurally-Coupled Dual Uncertainty-Aware 3DGS SLAM in the Wild13 Sep 2026
- 2026Point4D: Long-range 4D Motion Reconstruction8 Sep 2026
- 2026A Calibration Audit of Confidence in Feed-Forward 3D Reconstruction Models30 Aug 2026
- 2026RoSe-SLAM: Robust Semantic-Aware Gaussian Splatting SLAM from Dynamic Monocular Videos29 Aug 2026
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