Den-SOFT: Dense Space-Oriented Light Field DataseT for 6-DOF Immersive
  Experience
Xiaohang Yu Zhengxian Yang Shi Pan Yuqi Han Haoxiang Wang Jun Zhang Shi Yan Borong Lin Lei Yang Tao Yu Lu Fang
We have built a custom mobile multi-camera large-space dense light field
capture system, which provides a series of high-quality and sufficiently dense
light field images for various scenarios. Our aim is to contribute to the
development of popular 3D scene reconstruction algorithms such as IBRnet, NeRF,
and 3D Gaussian splitting. More importantly, the collected dataset, which is
much denser than existing datasets, may also inspire space-oriented light field
reconstruction, which is potentially different from object-centric 3D
reconstruction, for immersive VR/AR experiences. We utilized a total of 40
GoPro 10 cameras, capturing images of 5k resolution. The number of photos
captured for each scene is no less than 1000, and the average density (view
number within a unit sphere) is 134.68. It is also worth noting that our system
is capable of efficiently capturing large outdoor scenes. Addressing the
current lack of large-space and dense light field datasets, we made efforts to
include elements such as sky, reflections, lights and shadows that are of
interest to researchers in the field of 3D reconstruction during the data
capture process. Finally, we validated the effectiveness of our provided
dataset on three popular algorithms and also integrated the reconstructed 3DGS
results into the Unity engine, demonstrating the potential of utilizing our
datasets to enhance the realism of virtual reality (VR) and create feasible
interactive spaces. The dataset is available at our project website.