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A radiance field is an effective representation of 3D scenes, which has beenwidely adopted in novel-view synthesis and 3D reconstruction. It is still anopen and challenging problem to evaluate the geometry, i.e., the density field,as the ground-truth is almost impossible to obtain. One alternative indirectsolution is to transform the density field into a point-cloud and compute itsChamfer Distance with the scanned ground-truth. However, many widely-useddatasets have no point-cloud ground-truth since the scanning process along withthe equipment is expensive and complicated. To this end, we propose a novelmetric, named Inverse Mean Residual Color (IMRC), which can evaluate thegeometry only with the observation images. Our key insight is that the betterthe geometry, the lower-frequency the computed color field. From this insight,given a reconstructed density field and observation images, we design aclosed-form method to approximate the color field with low-frequency sphericalharmonics, and compute the inverse mean residual color. Then the higher theIMRC, the better the geometry. Qualitative and quantitative experimentalresults verify the effectiveness of our proposed IMRC metric. We also benchmarkseveral state-of-the-art methods using IMRC to promote future related research.Our code is available at https://github.com/qihangGH/IMRC.

Evaluate Geometry of Radiance Fields with Low-frequency Color Prior