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Computer Vision Group
TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich

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Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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News

26.02.2025

We have twelve papers accepted to CVPR 2025. Check our publication page for more details.

24.10.2024

LSD SLAM received the ECCV 2024 Koenderink Award for standing the Test of Time.

03.07.2024

We have seven papers accepted to ECCV 2024. Check our publication page for more details.

09.06.2024
GCPR / VMV 2024

GCPR / VMV 2024

We are organizing GCPR / VMV 2024 this fall.

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

More


Dataset Download

We provide several types of sequences for evaluating visual odometry, global place recognition, and map-based re-localization tracking algorithms:

  • Office Loop : A loop around an industrial area of the city.
  • Highway : A loop on the A9 highway in the north part of Munich.
  • Neighborhood : Traversal through a regular neighborhood at the outskirts of the city covering detached houses with gardens and trees in the street.
  • Business Campus : Several loops around a campus in a business area around the city.
  • Countryside : Rural area around agricultural fields which exhibits very homogeneous and repetitive structures. The scene shows heavy vegetation.
  • City Loop : A large-scale loop at a ring road within the city of Munich including a tunnel.
  • Old Town : Loop around the urban city center with tall buildings, much traffic, and dynamic objects.
  • Maximilianeum : The Maximilianeum is a famous palatial building in Munich which is located at the eastern end of a royal avenue with paving stones and a tram route.
  • Parking Garage : A multi-level (three levels) parking garage to benchmark combined indoor/outdoor environments.

All sequences have been processed to have:

  • consistent timestamps for camera, IMU, and reference poses
  • raw RTK-GNSS measurements
  • distorted/undistorted stereo images

Office Loop

Sequence name Tags IMU Point clouds Reference poses Stereo images (distorted) Stereo images (undistorted) Preview Video
office_loop_1_train spring,sunny,afternoon zip (19MB) zip (49MB) zip (1.1MB) zip (4.5GB) zip (4.2GB) play (5x)
office_loop_2_train spring,sunny,afternoon zip (16MB) zip (46MB) zip (905KB) zip (3.8GB) zip (3.6GB) play (5x)
office_loop_3_train spring,sunny,morning zip (19MB) zip (65MB) zip (1.1MB) zip (4.6GB) zip (4.3GB) play (5x)
office_loop_4_train summer,sunny,morning zip (18MB) zip (75MB) zip (1.1MB) zip (4.5GB) zip (4.2GB) play (5x)
office_loop_5_train winter,cloudy/snowy,afternoon zip (18MB) zip (63MB) zip (981KB) zip (4.1GB) zip (3.8GB) play (5x)
office_loop_6_train winter,sunny,afternoon zip (18MB) zip (63MB) zip (1005KB) zip (4.5GB) zip (4.2GB) play (5x)
office_loop_2_test spring,cloudy/sunny,afternoon zip (16MB) zip (3.8GB) zip (3.6GB) play (5x)
office_loop_3_test spring,cloudy,evening zip (16MB) zip (3.5GB) zip (3.2GB) play (5x)

Highway

Sequence name Tags IMU Point clouds Reference poses Stereo images (distorted) Stereo images (undistorted) Preview Video
highway_1_test fall,sunny,morning zip (13MB) zip (2.7GB) zip (2.5GB) play (5x)
highway_2_test winter,sunny,afternoon zip (12MB) zip (2.5GB) zip (2.2GB) play (5x)

Neighborhood

Sequence name Tags IMU Point clouds Reference poses Stereo images (distorted) Stereo images (undistorted) Preview Video
neighborhood_1_train spring,cloudy,afternoon zip (14MB) zip (41MB) zip (761KB) zip (3.3GB) zip (3.2GB) play (5x)
neighborhood_2_train fall,cloudy,afternoon zip (13MB) zip (46MB) zip (710KB) zip (2.9GB) zip (2.7GB) play (5x)
neighborhood_3_train fall,rainy,afternoon zip (12MB) zip (42MB) zip (672KB) zip (2.7GB) zip (2.5GB) play (5x)
neighborhood_4_train winter,cloudy,morning zip (13MB) zip (37MB) zip (684KB) zip (2.7GB) zip (2.5GB) play (5x)
neighborhood_5_train winter,sunny,afternoon zip (12MB) zip (40MB) zip (649KB) zip (2.8GB) zip (2.7GB) play (5x)
neighborhood_6_train spring,cloudy,evening zip (15MB) zip (44MB) zip (807KB) zip (3.3GB) zip (3.1GB) play (5x)
neighborhood_7_train spring,cloudy,evening zip (14MB) zip (44MB) zip (753KB) zip (3.1GB) zip (2.9GB) play (5x)
neighborhood_2_test spring,cloudy,evening zip (13MB) zip (2.9GB) zip (2.6GB) play (5x)

Business Campus

Sequence name Tags IMU Point clouds Reference poses Stereo images (distorted) Stereo images (undistorted) Preview Video
business_campus_1_train fall,sunny,morning zip (20MB) zip (38MB) zip (759KB) zip (5.1GB) zip (4.9GB) play (5x)
business_campus_2_train winter,cloudy/snowy,afternoon zip (16MB) zip (56MB) zip (855KB) zip (3.3GB) zip (3.1GB) play (5x)
business_campus_3_train winter,sunny,afternoon zip (16MB) zip (60MB) zip (895KB) zip (3.6GB) zip (3.4GB) play (5x)
business_campus_1_test winter,cloudy/snowy,afternoon zip (16MB) zip (3.6GB) zip (3.3GB) play (5x)

Countryside

Sequence name Tags IMU Point clouds Reference poses Stereo images (distorted) Stereo images (undistorted) Preview Video
countryside_1_train spring,sunny,morning zip (20MB) zip (92MB) zip (1.2MB) zip (4.2GB) zip (3.7GB) play (5x)
countryside_2_train summer,sunny,morning zip (22MB) zip (110MB) zip (1.3MB) zip (5.1GB) zip (4.6GB) play (5x)
countryside_3_train fall,sunny,morning zip (19MB) zip (85MB) zip (1.1MB) zip (4.1GB) zip (3.7GB) play (5x)
countryside_4_train winter,cloudy/snowy,afternoon zip (19MB) zip (92MB) zip (1.1MB) zip (4.1GB) zip (3.6GB) play (5x)
countryside_2_test winter,cloudy/snowy,afternoon zip (18MB) zip (3.4GB) zip (3.0GB) play (5x)

City Loop

Sequence name Tags IMU Point clouds Reference poses Stereo images (distorted) Stereo images (undistorted) Preview Video
city_loop_1_train winter,rainy,morning zip (36MB) zip (87MB) zip (2.0MB) zip (8.0GB) zip (7.2GB) play (5x)
city_loop_2_train winter,snowy/sunny,afternoon zip (32MB) zip (126MB) zip (1.9MB) zip (6.9GB) zip (6.4GB) play (5x)
city_loop_3_train winter,sunny,morning zip (34MB) zip (147MB) zip (2.0MB) zip (8.4GB) zip (7.8GB) play (5x)
city_loop_2_test winter,sunny,morning zip (35MB) zip (6.4GB) zip (6.0GB) play (5x)

Old Town

Sequence name Tags IMU Point clouds Reference poses Stereo images (distorted) Stereo images (undistorted) Preview Video
old_town_1_train fall,cloudy,morning zip (32MB) zip (78MB) zip (1.9MB) zip (8.1GB) zip (7.7GB) play (5x)
old_town_2_train winter,cloudy/snowy/sunny,morning zip (29MB) zip (75MB) zip (1.6MB) zip (5.9GB) zip (5.5GB) play (5x)
old_town_3_train winter,sunny,afternoon zip (32MB) zip (80MB) zip (1.8MB) zip (8.6GB) zip (8.3GB) play (5x)
old_town_4_train spring,cloudy,night zip (28MB) zip (43MB) zip (1.6MB) zip (3.3GB) zip (3.1GB) play (5x)
old_town_2_test spring,cloudy,evening zip (27MB) zip (6.8GB) zip (6.5GB) play (5x)
old_town_3_test spring,cloudy,night zip (28MB) zip (3.4GB) zip (3.2GB) play (5x)

Maximilianeum

Sequence name Tags IMU Point clouds Reference poses Stereo images (distorted) Stereo images (undistorted) Preview Video
maximilianeum_1_test winter,sunny,afternoon zip (18MB) zip (4.5GB) zip (4.4GB) play (5x)
maximilianeum_2_test spring,cloudy,night zip (18MB) zip (2.0GB) zip (1.9GB) play (5x)

Parking Garage

Sequence name Tags IMU Point clouds Reference poses Stereo images (distorted) Stereo images (undistorted) Preview Video
parking_garage_1_train winter,cloudy,afternoon zip (8.8MB) zip (29MB) zip (542KB) zip (1.8GB) zip (1.7GB) play (5x)
parking_garage_2_train winter,sunny,afternoon zip (6.6MB) zip (25MB) zip (395KB) zip (1.4GB) zip (1.3GB) play (5x)
parking_garage_3_train spring,cloudy,evening zip (6.1MB) zip (19MB) zip (371KB) zip (1.3GB) zip (1.2GB) play (5x)
parking_garage_1_test summer,sunny,morning zip (5.2MB) zip (1.2GB) zip (1.1GB) play (5x)

Calibration

The calibration folder contains intrinsics and extrinsics of our sensors.

calibration/calib_0.txt

Intrinsic parameters of the left camera. Camera model, fx, fy, cx, cy, distortion coefficients.

calibration/calib_1.txt

Intrinsic parameters of the right camera. Camera model, fx, fy, cx, cy, distortion coefficients.

calibration/calib_stereo.txt

A 4x4 matrix denoting the rigid transformation from the right to the left camera.

calibration/undistorted_calib_0.txt

Intrinsic parameters of the left camera. Camera model, fx, fy, cx, cy, distortion coefficients.

calibration/undistorted_calib_1.txt

Intrinsic parameters of the right camera. Camera model, fx, fy, cx, cy, distortion coefficients.

calibration/undistorted_calib_stereo.txt

A 4x4 matrix denoting the rigid transformation from the right to the left camera.

calibration/camchain.yaml

Intrinsics and extrinsics for both cameras together in .yaml format.

Download calibration: calibration.zip (3KB)

Calibration Sequences

We provide calibration sequences for camera and IMU calibration.

camera_plus_imu_calibration.zip (1.8GB)

MD5 Checksums

Map Overlay / Point Cloud Preview

recording_2020-10-07_14-47-51 Point cloud preview
recording_2020-10-07_14-53-52 Point cloud preview
recording_2020-10-08_09-57-28 Point cloud preview
recording_2020-10-08_11-53-41 Point cloud preview
recording_2020-12-22_11-33-15 Point cloud preview
recording_2020-12-22_11-54-24 Point cloud preview
recording_2020-12-22_12-04-35 Point cloud preview
recording_2021-01-07_10-49-45 Point cloud preview
recording_2021-01-07_12-04-03 Point cloud preview
recording_2021-01-07_13-12-23 Point cloud preview
recording_2021-01-07_13-30-07 Point cloud preview
recording_2021-01-07_14-36-17 Point cloud preview
recording_2021-02-25_11-09-49 Point cloud preview
recording_2021-02-25_12-34-08 Point cloud preview
recording_2021-02-25_13-25-15 Point cloud preview
recording_2021-02-25_13-39-06 Point cloud preview
recording_2021-02-25_13-51-57 Point cloud preview
recording_2021-02-25_14-16-43 Point cloud preview

Rechte Seite

Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:

YouTube X / Twitter Facebook

News

26.02.2025

We have twelve papers accepted to CVPR 2025. Check our publication page for more details.

24.10.2024

LSD SLAM received the ECCV 2024 Koenderink Award for standing the Test of Time.

03.07.2024

We have seven papers accepted to ECCV 2024. Check our publication page for more details.

09.06.2024
GCPR / VMV 2024

GCPR / VMV 2024

We are organizing GCPR / VMV 2024 this fall.

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

More