Abstract: To address the imbalance between efficiency and accuracy in neural implicit surface reconstruction caused by dense sampling and volumetric rendering, an efficient reconstruction method is proposed. First, dynamic occupancy grids with density thresholds were used to select effective sampling points, reducing redundant computation and memory usage. Then, multi-resolution hash encoding was integrated with the Truncated Signed Distance Field (TSDF) to enhance gradient stability and noise resistance through truncated distance constraints and hash feature interpolation. Finally, photometric consistency was enforced across views using Normalized Cross-Correlation（NCC）. On the NeRF-Synthetic dataset, The proposed method reduced training time by 98.8% compared to Neural Radiance Fields (NeRF), with significantly better surface reconstruction quality than Instant-NGP. On the DTU dataset, the method achieved a Chamfering distance(CD) and Peak Signal to Noise Ratio(PSNR), outperforming Instant-NGP by 1.21 mm and 2.93 dB, respectively. Though slightly behind State Of The Arts (SOTA) Neuralangelo (with CD higher by 0.02 mm and PSNR lower by 2.05 dB) while reducing training time by 97.5% compared to Neuralangelo. The results demonstrate its effectiveness in achieving fast and accurate 3D reconstruction in complex scenes.

Key words: implicit neural surface, 3D reconstruction, Truncated Signed Distance Field (TSDF), dynamic occupancy grid, photometric consistency constraint

摘要： 针对隐式神经表面重建中密集采样及体积渲染导致的效率与精度失衡问题，提出一种快速高效重建方法。首先，采用动态占用网格结合密度阈值优化筛选有效采样点，降低冗余计算和内存占用；其次，融合多分辨率哈希编码和截断符号距离场（TSDF），通过截断距离约束和哈希特征插值增强梯度稳定性与抗噪能力；最后，引入光度一致性约束，利用归一化交叉相关（NCC）优化跨视角几何一致性，提高表面重建质量。在仿真数据集Nerf-Synthetic上，所提方法的训练时间相较于神经辐射场（NeRF）缩短了98.8%，虽比采用CUDA加速的Instant-NGP高，但表面重建质量得到明显提升。在真实数据集DTU上，该方法实验结果的表面重建误差倒角距离(CD)、新视角合成指标峰值信噪比(PSNR)远超大多数现有方法，较Instant-NGP分别降低1.21 mm和提高2.93 dB，虽略逊于SOTA(State Of The Arts)的Neuralangelo（CD 提升0.02 mm、PSNR 降低2.05 dB），但是训练耗时相较于Neuralangelo缩短了97.5%。结果表明，该方法能够有效提升训练效率且保证重建精度，实用性好，适用于复杂结构场景的高效三维重建。

关键词: 隐式神经表面, 三维重建, 截断符号距离场, 动态占用网格, 光度一致性约束