Datasets › KITTI-Masks
KITTI-Masks
This Dataset consists of 2120 sequences of binary masks of pedestrians. The sequence length varies between 2-710. For details, we refer to our paper. It is based on the original KITTI Segmentation challenge which can be found at https://www.vision.rwth-aachen.de/page/mots
A detailed description can be found at: https://openreview.net/pdf?id=EbIDjBynYJ8
An example dataloader can be found at: https://github.com/bethgelab/slow_disentanglement/
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 | ||||
|---|---|---|---|---|---|---|
| Disentanglement | KITTI-Masks | InfoNCE (Laplace, Box) MCC 80.9 | Contrastive Learning Inverts the Data Generating Process | brendel-group/cl-ica | 2 | Compare |
Papers archive 2025-07-28
2 shown of 2 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 3. 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 | |||
|---|---|---|---|---|
| Contrastive Learning Inverts the Data Generating Process | 1 | 1 | 17 Feb 2021 | ran 1 of 2 samples (1 unverified) |
| Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding | 1 | 1 | 21 Jul 2020 | ran 1 of 4 samples (3 unverified) |
Dataset loaders archive 2025-07-28
1 loader as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
License archive 2025-07-28
Creative Commons Attribution 4.0 International
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- KITTI-Masks
1 variant name, as the archive lists them.
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