EyefulTower
Official release of the Eyeful Tower dataset, a high-fidelity multi-view capture of 11 real-world scenes, from the paper “VR-NeRF High-Fidelity Virtualized Walkable Spaces” (Xu et al., SIGGRAPH Asia 2023).
Install / Use
/learn @facebookresearch/EyefulTowerREADME
Dataset Overview
Scene | ver | cams | pos | img | 2K<br>EXRs | 1K<br>EXRs | 8K+<br>JPEGs | 4K<br>JPEGs | 2K<br>JPEGs | 1K<br>JPEGs :------------------------------------------- | --- | -----------------------------------------------------------------------------------------------------------------------------------: | --: | ----: | --------------------------------------------------------------------------------------------------------------------------------------: | -------------------------------------------------------------------------------------------------------------------------------------: | ----------------------------------------------------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------------------: | --------------------------------------------------------------------------------------------------------------------------------------: [apartment][apartment_index] | v2 | 22 | 180 | 3,960 | 123 GB | 31 GB | 92 GB | 20 GB | 5 GB | 1.2 GB [kitchen][kitchen_index] | v2* | 19 | 318 | 6,024 | 190 GB | 48 GB | 142 GB | 29 GB | 8 GB | 1.9 GB [office1a][office1a_index] | v1 | 9 | 85 | 765 | 24 GB | 6 GB | 15 GB | 3 GB | 1 GB | 0.2 GB [office1b][office1b_index] | v2 | 22 | 71 | 1,562 | 49 GB | 13 GB | 35 GB | 7 GB | 2 GB | 0.4 GB [office2][office2_index] | v1 | 9 | 233 | 2,097 | 66 GB | 17 GB | 46 GB | 9 GB | 2 GB | 0.5 GB [office_view1][office_view1_index] | v2 | 22 | 126 | 2,772 | 87 GB | 22 GB | 63 GB | 14 GB | 4 GB | 0.8 GB [of
