nvibd commited on
Commit
2521064
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1 Parent(s): 83063e5

Reorganize dataset: per-scene zips for COLMAP and NCore V4 formats

Browse files
README.md CHANGED
@@ -9,6 +9,7 @@ tags:
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  - novel-view-synthesis
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  - radiance-fields
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  - photometric-calibration
 
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  pretty_name: PPISP Dataset
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  size_categories:
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  - 1K<n<10K
@@ -21,6 +22,8 @@ The PPISP dataset accompanies the work "PPISP: Physically-Plausible Compensation
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  Each scene has two variants: a standard version processed from the full exposure brackets, and an auto version where selected exposures were re-processed with automatic exposure compensation and white balancing, for a total of eight sequences. We also provide pre-computed COLMAP sparse reconstructions (camera poses and point clouds) for each sequence, enabling direct usage in common radiance field reconstruction methods.
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  This dataset is ready for commercial/non-commercial use.
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  ## Dataset Owner(s):
@@ -47,12 +50,13 @@ The raw photos were developed to JPEG using the manufacturer's recommended softw
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  We used COLMAP to reconstruct camera poses and a sparse point cloud for each sequence.
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  ## Dataset Format
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- Downsampled images in JPEG format, COLMAP camera poses, COLMAP sparse point cloud.
 
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  ## Dataset Quantification
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  8 sequences, about 2600 photos in JPEG format total. The four standard sequences contain 500-700 images each; the four auto sequences contain 50-150 images each.
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- Measurement of Total Data Storage: About 7.5 GB in compressed form.
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  ## Reference(s):
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  [Project Page](https://research.nvidia.com/labs/sil/projects/ppisp/)
 
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  - novel-view-synthesis
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  - radiance-fields
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  - photometric-calibration
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+ - ncore
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  pretty_name: PPISP Dataset
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  size_categories:
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  - 1K<n<10K
 
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  Each scene has two variants: a standard version processed from the full exposure brackets, and an auto version where selected exposures were re-processed with automatic exposure compensation and white balancing, for a total of eight sequences. We also provide pre-computed COLMAP sparse reconstructions (camera poses and point clouds) for each sequence, enabling direct usage in common radiance field reconstruction methods.
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+ The dataset is provided in two formats: COLMAP (`colmap/`) and NCore V4 (`ncore/`). Each format contains one zip archive per scene, with both the standard and auto variants as separate folders (e.g., `huerstholz/` and `huerstholz_auto/`).
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+
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  This dataset is ready for commercial/non-commercial use.
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  ## Dataset Owner(s):
 
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  We used COLMAP to reconstruct camera poses and a sparse point cloud for each sequence.
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  ## Dataset Format
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+ - **COLMAP format** (`colmap/`): Downsampled images in JPEG format, COLMAP camera poses, COLMAP sparse point cloud.
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+ - **NCore V4 format** (`ncore/`): NCore V4 scene archives and metadata.
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  ## Dataset Quantification
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  8 sequences, about 2600 photos in JPEG format total. The four standard sequences contain 500-700 images each; the four auto sequences contain 50-150 images each.
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+ Measurement of total data storage: About 14.3 GB in compressed form (8.1 GB COLMAP format + 6.2 GB NCore V4 format).
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  ## Reference(s):
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  [Project Page](https://research.nvidia.com/labs/sil/projects/ppisp/)
ppisp_dataset.zip → colmap/huerstholz_colmap.zip RENAMED
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