Datasets › Deep Blending
Deep Blending
The Deep Blending Dataset comprises 19 diverse scenes, offering comprehensive resources for free-viewpoint image-based rendering (IBR). Each scene includes input images, COLMAP reconstructions (SfM & MVS), global textured meshes from RealityCapture, refined depth maps, per-view meshes, and camera poses. This dataset is ideal for training and evaluating novel view synthesis and blending algorithms in both indoor and outdoor environments.
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Novel View Synthesis | Deep Blending | Self-Organizing Gaussians LPIPS 0.258 | Compact 3D Scene Representation via Self-Organizing... | facebookresearch/uco3d +1 | 1 | Compare |
Papers archive 2025-07-28
1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 2. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| Compact 3D Scene Representation via Self-Organizing Gaussian Grids | 2 | 1 | 19 Dec 2023 | ran 1 of 1 samples (0 unverified; 1 pointer-only for licence) |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
No variants listed.
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