On June 17th, Youngju Na presented his recent research, UFORecon, at CVPR 2024, Seattle. The proposed work addresses the problem of generalizable surface reconstruction given a limited number of multi-view images under arbitrary and unfavorably captured conditions. It introduced a novel concept called “view-combination generalizability” in the few-shot NeRF scheme and effectively addressed it with a correlation-aware volume rendering pipeline.
