Summary of Gennbv: Generalizable Next-best-view Policy For Active 3d Reconstruction, by Xiao Chen and Quanyi Li and Tai Wang and Tianfan Xue and Jiangmiao Pang
GenNBV: Generalizable Next-Best-View Policy for Active 3D Reconstruction
by Xiao Chen, Quanyi Li, Tai Wang, Tianfan Xue, Jiangmiao Pang
First submitted to arxiv on: 25 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes an end-to-end generalizable Next-Best-View (NBV) policy for active 3D reconstruction called GenNBV. The existing NBV policies rely heavily on hand-crafted criteria, limited action space, or per-scene optimized representations, which limits their cross-dataset generalizability. To overcome these constraints, the authors use a reinforcement learning-based framework that extends the typical limited action space to 5D free space, allowing the agent drone to scan from any viewpoint and even interact with unseen geometries during training. The policy is evaluated using the Isaac Gym simulator with the Houses3K and OmniObject3D datasets, achieving a 98.26% and 97.12% coverage ratio on unseen building-scale objects from these datasets, respectively. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper makes it possible to automatically capture images of large scenes in a more efficient way. Currently, this process is time-consuming and requires a lot of labor. The researchers developed a new method called GenNBV that allows an agent drone to find the best view to capture from any angle and even interact with objects it hasn’t seen before. This makes the method more flexible and able to work well on different scenes. The authors tested their method using computer simulations and found that it can capture images of buildings at a high success rate. |
Keywords
» Artificial intelligence » Reinforcement learning
