Heterogeneous Dataset Acquisition for a Continuously Expandable Benchmark (CEB)

Ongoing research within the field of computer vision yielded a wide range of image based 3D reconstruction approaches. Starting years ago with low resolution RGB images as input, we face today a wide and fast growing range of available imaging devices to perform this task. To allow for a good comparability of resulting reconstructions, many different benchmarks and datasets have been made available. At the same time, we observe, that these benchmarks commonly address only a single capturing approach omitting the chance to compare against results of other acquisition methods. In contrast to such homogeneous benchmarks, we present in this work a heterogeneous benchmark, considering different acquisition devices to obtain our datasets. Besides these datasets, we furthermore provide reference data for download. To lastly keep track of the rapidly increasing number of different acquisition sensors, we opt to provide occasional updates of this benchmark within the future.