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Poster

Explaining Human Preferences via Metrics for Structured 3D Reconstruction

Jack Langerman · Denis Rozumny · Yuzhong Huang · Dmytro Mishkin

Exhibit Hall I #2489
Highlight Award Highlight
[ ] [ Project Page ]
Thu 23 Oct 5:45 p.m. PDT — 7:45 p.m. PDT

Abstract:

What cannot be measured cannot be improved while likely never uttered by Lord Kelvin, summarizes effectively the purpose of this work. This paper presents a detailed evaluation of automated metrics for evaluating structured 3D reconstructions. Pitfalls of each metric are discussed, and a thorough analyses through the lens of expert 3D modelers' preferences is presented. A set of systematic "unit tests" are proposed to empirically verify desirable properties, and context aware recommendations as to which metric to use depending on application are provided. Finally, a learned metric distilled from human expert judgments is proposed and analyzed.

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