3D拡散モデルの事前分布を活用したRGB画像からのワンショット視点計画
Exploiting Priors from 3D Diffusion Models for RGB-Based One-Shot View Planning
3D拡散モデルが生成する形状事前分布を利用し、対象物体のRGB画像1枚だけから効率的な視点計画を一度に行う手法を提案した。
著者: Sicong Pan, Liren Jin, Xuying Huang, Cyrill Stachniss, Marija Popović, Maren Bennewitz
分類: cs.RO, cs.CV
原文アブストラクト
Object reconstruction is relevant for many autonomous robotic tasks that require interaction with the environment. A key challenge in such scenarios is planning view configurations to collect informative measurements for reconstructing an initially unknown object. One-shot view planning enables efficient data collection by predicting view configurations and planning the globally shortest path connecting all views at once. However, prior knowledge about the object is required to conduct one-shot view planning. In this work, we propose a novel one-shot view planning approach that utilizes the powerful 3D generation capabilities of diffusion models as priors. By incorporating such geometric priors into our pipeline, we achieve effective one-shot view planning starting with only a single RGB image of the object to be reconstructed. Our planning experiments in simulation and real-world setups indicate that our approach balances well between object reconstruction quality and movement cost.
