We introduce Omni-LOS, a neural computational imaging method for conducting holistic shape reconstruction (HSR) of complex objects utilizing a Single-Photon Avalanche Diode (SPAD)-based time-of-flight sensor. As illustrated in Fig. 1, our method enables new capabilities to reconstruct near-$360^\circ$ surrounding geometry of an object from a single scan spot. In such a scenario, traditional line-of-sight (LOS) imaging methods only see the front part of the object and typically fail to recover the occluded back regions. Inspired by recent advances of non-line-of-sight (NLOS) imaging techniques which have demonstrated great power to reconstruct occluded objects, Omni-LOS marries LOS and NLOS together, leveraging their complementary advantages to jointly recover the holistic shape of the object from a single scan position. The core of our method is to put the object nearby diffuse walls and augment the LOS scan in the front view with the NLOS scans from the surrounding walls, which serve as virtual ``mirrors'' to trap lights toward the object. Instead of separately recovering the LOS and NLOS signals, we adopt an implicit neural network to represent the object, analogous to NeRF and NeTF. While transients are measured along straight rays in LOS but over the spherical wavefronts in NLOS, we derive differentiable ray propagation models to simultaneously model both types of transient measurements so that the NLOS reconstruction also takes into account the direct LOS measurements and vice versa. We further develop a proof-of-concept Omni-LOS hardware prototype for real-world validation. Comprehensive experiments on various wall settings demonstrate that Omni-LOS successfully resolves shape ambiguities caused by occlusions, achieves high-fidelity 3D scan quality, and manages to recover objects of various scales and complexity.

翻译：我们提出Omni-LOS，一种基于单光子雪崩二极管（SPAD）飞行时间传感器的神经计算方法，用于实现复杂物体的全方位形状重建（HSR）。如图1所示，该方法能从单一扫描点重建物体近360°环绕几何结构。在此场景下，传统视域内成像方法仅能观测物体前部，无法恢复被遮挡的后部区域。受近年来非视域成像技术在重建遮挡物体方面取得重大进展的启发，Omni-LOS融合视域内与非视域成像技术，利用两者的互补优势从单一扫描位置联合恢复物体完整形状。该方法的核心在于将物体置于漫反射墙体附近，将前向视域内的视域扫描与周边墙体的非视域扫描相结合——这些墙体充当虚拟"镜面"将光线导向物体。不同于分别恢复视域与非视域信号，我们借鉴NeRF和NeTF思想采用隐式神经网络表征物体。针对视域内沿直线传播的瞬态测量与非视域中沿球面波前的瞬态测量特性，我们推导了可微分的射线传播模型同步建模两类瞬态测量数据，使非视域重建同时考虑视域测量结果，反之亦然。我们进一步搭建了概念验证型Omni-LOS硬件原型进行实际验证。在多种墙体配置下的全面实验表明，Omni-LOS成功解决了遮挡造成的形状歧义，实现了高保真三维扫描质量，并能够恢复不同尺度与复杂度的物体。