Kavli Affiliate: Cheng Peng
| First 5 Authors: Xijun Liu, Yifan Zhou, Yuxiang Guo, Rama Chellappa, Cheng Peng
| Summary:
Significant progress has been made in photo-realistic scene reconstruction
over recent years. Various disparate efforts have enabled capabilities such as
multi-appearance or large-scale modeling; however, there lacks a welldesigned
dataset that can evaluate the holistic progress of scene reconstruction. We
introduce a collection of imagery of the Johns Hopkins Homewood Campus,
acquired at different seasons, times of day, in multiple elevations, and across
a large scale. We perform a multi-stage calibration process, which efficiently
recover camera parameters from phone and drone cameras. This dataset can enable
researchers to rigorously explore challenges in unconstrained settings,
including effects of inconsistent illumination, reconstruction from large scale
and from significantly different perspectives, etc.
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