Datasets:
pretty_name: IH-Depth
license: cc-by-4.0
task_categories:
- depth-estimation
size_categories:
- n<1K
configs:
- config_name: default
data_files:
- split: train
path: scenes_train.csv
- split: test
path: scenes_test.csv
Dataset Card for IH-Depth
IH-Depth is a benchmark for metric depth estimation from long-wave hyperspectral imagery (LWHSI) in off-road scenes. The benchmark is derived from the Invisible Headlights (IH) dataset and pairs raw LWHSI scenes with sparse LiDAR-projected depth labels.
IH-Depth contains 51 released scenes split into 41 training scenes and 10 test scenes. Download the dataset into the same directory as the raw IH dataset so each released depth PNG lands beside the matching raw .hdr and .bsq LWHSI files.
More details on usage, evaluation, and reference baselines can be found in the IH-Depth GitHub repository.
Dataset Contents
Each released scene contains one IH-Depth artifact named with the same stem as the corresponding raw LWHSI file. Here, <raw_lwhsi_stem> means the raw LWHSI filename without the .hdr or .bsq extension. For example, if the raw files are IHTest_202009_Path3_Step6_LWHSI1__DistStA.hdr and IHTest_202009_Path3_Step6_LWHSI1__DistStA.bsq, then <raw_lwhsi_stem> is IHTest_202009_Path3_Step6_LWHSI1__DistStA.
<raw_lwhsi_stem>_depth.png
The depth maps are sparse metric labels projected from LiDAR into the LWHSI image. Depth PNGs follow a KITTI-style 16-bit encoding:
dtype: uint16
stored_value = round(128 * depth_m)
0 = invalid / unlabeled
depth_m = stored_value / 128
Dataset Structure
Only the depth PNGs are meant to be stored in the raw IH tree beside the matching raw files. A released depth-labeled scene has the form:
<RAW_IH_ROOT>/
<collection>/
<PathXX_DistStA>/
<PathXX_StepYY...>/
<raw_lwhsi_stem>.hdr
<raw_lwhsi_stem>.bsq
<raw_lwhsi_stem>_depth.png
The release root contains:
scenes_train.csv
scenes_test.csv
scenes_manifest.csv
README.md
The scene CSV files define the IH-Depth benchmark splits and artifact paths. These split files are part of IH-Depth and are not part of the raw IH dataset.
Data Stats
To characterize scene diversity, RGB visualizations of the released scenes were assigned to six primary scene categories and manually reviewed for consistency:
| Scene category | Share | Scenes |
|---|---|---|
| Open fields | 33.3% | 17 |
| Sandy scrub | 31.4% | 16 |
| Utility corridors | 13.7% | 7 |
| Built industrial areas | 13.7% | 7 |
| Forests | 5.9% | 3 |
| Water | 2.0% | 1 |
This diversity reflects the off-road and mixed-terrain nature of IH-Depth: the benchmark is not limited to a single road layout, vegetation pattern, or background structure, but instead evaluates metric depth estimation across varied LWHSI conditions.
License
IH-Depth is released under the CC BY 4.0 license. The raw Invisible Headlights dataset is distributed separately under its own terms.