Despite the tremendous progress in neural radiance fields (NeRF), we still face a dilemma of the trade-off between quality and efficiency, e.g., MipNeRF presents fine-detailed and anti-aliased renderings but takes days for training, while Instant-ngp can accomplish the reconstruction in a few minutes but suffers from blurring or aliasing when rendering at various distances or resolutions due to ignoring the sampling area. To this end, we propose a novel Tri-Mip encoding that enables both instant reconstruction and anti-aliased high-fidelity rendering for neural radiance fields. The key is to factorize the pre-filtered 3D feature spaces in three orthogonal mipmaps. In this way, we can efficiently perform 3D area sampling by taking advantage of 2D pre-filtered feature maps, which significantly elevates the rendering quality without sacrificing efficiency. To cope with the novel Tri-Mip representation, we propose a cone-casting rendering technique to efficiently sample anti-aliased 3D features with the Tri-Mip encoding considering both pixel imaging and observing distance. Extensive experiments on both synthetic and real-world datasets demonstrate our method achieves state-of-the-art rendering quality and reconstruction speed while maintaining a compact representation that reduces 25% model size compared against Instant-ngp.

翻译：尽管神经辐射场（NeRF）取得了巨大进展，我们仍面临质量与效率之间的权衡困境：例如，MipNeRF虽能呈现精致细节和抗锯齿渲染，但训练需耗时数天；而Instant-ngp虽能在数分钟内完成重建，却因忽略采样区域而在不同距离或分辨率下渲染时出现模糊或锯齿现象。为此，我们提出一种新颖的三Mip编码方法，能够同时实现神经辐射场的即时重建与抗锯齿高保真渲染。其关键在于将预滤波的3D特征空间分解为三个正交的mipmap层级。通过这种方式，我们能够利用2D预滤波特征图高效执行3D区域采样，在显著提升渲染质量的同时不牺牲效率。为适配这一新型三Mip表示，我们提出一种锥体投射渲染技术，结合像素成像与观测距离，通过三Mip编码高效采样抗锯齿3D特征。在合成数据集与真实世界数据集上的大量实验表明，我们的方法在保持紧凑表示（相较于Instant-ngp模型尺寸减小25%）的同时，实现了最先进的渲染质量与重建速度。