Taiki Yoshino

HotSpot: Signed Distance Function Optimization with an Asymptotically Sufficient Condition

We propose a method, HotSpot, for optimizing neural signed distance functions. Existing losses, such as the eikonal loss, act as necessary but insufficient constraints and cannot guarantee that the recovered implicit function represents a true distance function, even if the output minimizes these lo…