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KITTI Vision Benchmark

The original self-driving benchmark — stereo, LiDAR, and 200K object labels from Karlsruhe.

LQS 86 · gold ⚠ Research-only 200K labeled objects 175 GB PNG · BIN Released 2012
Browse commercial Autonomous Vehicles → Visit original source ↗
Source: cvlibs.net · maintained by KIT / Toyota Technological Institute at Chicago
200K
labeled objects
175 GB
Size on disk
86
LQS · gold
2012
First released

About this dataset

KITTI from Karlsruhe Institute of Technology and Toyota Technological Institute is the original autonomous driving benchmark. Stereo camera, rotating LiDAR (Velodyne HDL-64E), and GPS/IMU data from driving in Karlsruhe, Germany. Object detection, tracking, odometry, and depth benchmarks. Still cited in most AV papers for legacy comparison.

License
Formats
PNG · BIN · TXT

LabelSets Quality Score

LQS is our 7-dimension quality score, computed from the dataset's published statistics. See methodology →

86
out of 100
gold tier

High-quality dataset across most dimensions

Composite score computed from the 7 dimensions below: completeness, uniqueness, validation health, size adequacy, format compliance, label density, and class balance.

Completeness 95
No public completeness metric; using prior for 'expert_curated' datasets.
Uniqueness 90
Benchmark-grade splits with leakage prevention.
Validation 92
Labels produced by domain experts or trained annotators.
Size adequacy 97
200,000 items — exceeds 1,000 adequacy target for Autonomous Vehicles.
Format compliance 82
Custom format, documented but non-standard.
Label density 52
Average 1.0 labels per item (sparse).
Class balance 75
Moderate class skew — realistic production distribution.

What it's used for

Common tasks and benchmarks where KITTI Vision Benchmark is the default or competitive choice.

Sample statistics

What's actually in the dataset — from the maintainer's published stats.

7,481 train + 7,518 test frames for object detection. 200K labeled objects across 8 classes. 42K km of driving data. Stereo + Velodyne HDL-64E.

License

KITTI Vision Benchmark is distributed under CC BY-NC-SA 3.0. This is a third-party public dataset; LabelSets indexes and scores it but does not host or redistribute the data. Always verify current license terms with the maintainer before commercial use.

Heads up: this dataset's license restricts commercial use. If you need autonomous vehicles data for production, check LabelSets' paid datasets below — every listing has an explicit commercial license.

Need commercial-licensed Autonomous Vehicles data?

LabelSets sellers offer paid autonomous vehicles datasets with what public datasets often can't give you:

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Similar public datasets

Other entries in the Autonomous Vehicles catalog.

Frequently Asked Questions

KITTI Vision Benchmark is distributed under CC BY-NC-SA 3.0, which restricts commercial use. For a commercially-licensed alternative in autonomous vehicles, see LabelSets' paid datasets.
KITTI Vision Benchmark contains 200,000 labeled objects. 7,481 train + 7,518 test frames for object detection. 200K labeled objects across 8 classes. 42K km of driving data. Stereo + Velodyne HDL-64E.
KITTI Vision Benchmark is maintained by KIT / Toyota Technological Institute at Chicago and is available at https://www.cvlibs.net/datasets/kitti/raw_data.php. LabelSets indexes and scores this dataset for discoverability but does not redistribute it.
LQS is a 7-dimension quality score (completeness, uniqueness, validation, size adequacy, format compliance, label density, class balance) computed from the dataset's published statistics. Composite scores map to tiers: platinum (≥90), gold (≥75), silver (≥60), bronze (<60). Read the full methodology.