Similar to the DTU results, using the analytical gradient
produces noisy surfaces and thus leads to a low F1 score.
We further note that the reconstruction of Courthouse shown
in Figs. 1 and 5 are the same building of different sides,
demonstrating the capability of Neuralangelo for large-scale
granular reconstruction.

4.3. Level of Details

As Neuralangelo progressively optimizes the hash fea-
tures of increasing resolution, we inspect the progressive
level of details similar to NGLOD [33]. We show a qualita-
tive visualization in Fig. 6. While some surfaces are entirely
missed by coarse levels, for example, the tree, table, and

InputAGAG+PNGNG+P (Ours)8461Figure 5. Qualitative comparison on Tanks and Temples dataset [15]. Neuralangelo captures the scene details better compared to other
baseline approaches, while baseline approaches have missing or noisy surfaces.
Neuralangelo- High-Fidelity Neural Surface Reconstruction