Datasets › Freiburg Forest
Freiburg Forest
The Freiburg Forest dataset was collected using a Viona autonomous mobile robot platform equipped with cameras for capturing multi-spectral and multi-modal images. The dataset may be used for evaluation of different perception algorithms for segmentation, detection, classification, etc. All scenes were recorded at 20 Hz with a camera resolution of 1024x768 pixels. The data was collected on three different days to have enough variability in lighting conditions as shadows and sun angles play a crucial role in the quality of acquired images. The robot traversed about 4.7 km each day. The dataset creators provide manually annotated pixel-wise ground truth segmentation masks for 6 classes: Obstacle, Trail, Sky, Grass, Vegetation, and Void.
Source: http://deepscene.cs.uni-freiburg.de/ Image Source: http://deepscene.cs.uni-freiburg.de/
Benchmarks archive 2025-07-28
All 2 leaderboards 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 | ||||
|---|---|---|---|---|---|---|
| Unsupervised Image-To-Image Translation | Freiburg Forest Dataset | In2I PSNR 21.65 | In2I : Unsupervised Multi-Image-to-Image Translation... | PramuPerera/In2I | 3 | Compare |
| Semantic Segmentation | Freiburg Forest | SSMA Mean IoU 84.18 | Self-Supervised Model Adaptation for Multimodal Semantic... | DeepSceneSeg/SSMA | 2 | Compare |
Papers archive 2025-07-28
4 shown of 4 papers 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 6. 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 | |||
|---|---|---|---|---|
| Self-Supervised Model Adaptation for Multimodal Semantic Segmentation | 1 | 2 | 11 Aug 2018 | not harvested |
| In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks | 1 | 1 | 26 Nov 2017 | not harvested |
| Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks | 190 | 1 | 30 Mar 2017 | ran 6 of 31 samples (25 unverified; 6 pointer-only for licence) |
| Unsupervised Image-to-Image Translation Networks | 8 | 1 | 2 Mar 2017 | ran 1 of 9 samples (8 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
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- Freiburg Forest
- Freiburg Forest Dataset
2 variant names, as the archive lists them.
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