Active Object Reconstruction Using a Guided View Planner
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Abstract (arXiv)
Inspired by the recent advance of image-based object reconstruction using deep learning, we present an active reconstruction model using a guided view planner. We aim to reconstruct a 3D model using images observed from a planned sequence of informative and discriminative views. But where are such informative and discriminative views around an object? To address this we propose a unified model for view planning and object reconstruction, which is utilized to learn a guided information acquisition model and to aggregate information from a sequence of images for reconstruction. Experiments show that our model (1) increases our reconstruction accuracy with an increasing number of views (2) and generally predicts a more informative sequence of views for object reconstruction compared to other alternative methods.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 May 2018.
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Citing papers per year: 2022: 3; 2023: 1; 2024: 0; 2025: 1.
5 papers.
- 2022Uncertainty-Driven Active Vision for Implicit Scene Reconstructioncited by 6
- 2022Point Cloud Scene Completion with Joint Color and Semantic Estimation from Single RGB-D Imagecited by 6
- 2023Interaction-Driven Active 3D Reconstruction with Object Interiorscited by 5
- 2022Explore Contextual Information for 3D Scene Graph Generationcited by 4
- 2025Touch2Shape: Touch-Conditioned 3D Diffusion for Shape Exploration and Reconstructioncited by 4
- 2025Touch2Shape: Touch-Conditioned 3D Diffusion for Shape Exploration and Reconstruction19 May 2025
- 2023Interaction-Driven Active 3D Reconstruction with Object Interiors23 Oct 2023
- 2022Explore Contextual Information for 3D Scene Graph Generation12 Oct 2022
- 2022Point Cloud Scene Completion with Joint Color and Semantic Estimation from Single RGB-D Image12 Oct 2022
- 2022Uncertainty-Driven Active Vision for Implicit Scene Reconstruction3 Oct 2022