EVIMO2v2

New projects should use EVIMO2v2 because it features temporal synchronization between sensors, less jitter, and a more efficient npz format as described here.

EVIMO2v1 is still available here.

Please refer to our documentation for detailed instructions on how to read and parse the data.

The authors would appreciate if you cite our papers:

  1. EVIMO2: An Event Camera Dataset for Motion Segmentation, Optical Flow, Structure from Motion, and Visual Inertial Odometry in Indoor Scenes with Monocular or Stereo Algorithms [bibtex]
  2. EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras [bibtex]
  3. Learning Visual Motion Segmentation Using Event Surfaces [bibtex]

The EVIMO2 Dataset

The Recording Setup

Prophesee Cameras (×2)

  • Resolution: 640×480
  • FOV: ~70°

Samsung DVS Gen3

  • Resolution: 640×480
  • FOV: ~75°

Flea3 (RGB)

  • Resolution: 2080×1552
  • FOV: ~65°

Prophesee Atis Gen3 (not used)

A picture of the rig with two prophese cameras on the sides, a samsung camera in the middle and a flea on the top

Tips for Downloading

A download script is provided here. The script saves about 350GB of disk space and an hour of extraction time by simultaneously downloading and extracting.

As discussed on GitHub, the kget download manager may help with downloading the files over unstable internet connections.

Downloading the full dataset requires approximately 350GB of bandwidth and 525GB (npz) or 842GB (txt) of disk space.

Excluding the flea3_7 RGB camera saves about 250GB of bandwidth and 271GB (npz) or 212GB (txt) of disk space.

Trying to decide between the npz and txt format? The information here might help.


Changelog

  • 02/14/2023 - NPZ extrinsics overlay is available here in response to a request on GitHub. Just extract it on top of the NPZ dataset.
  • 05/24/2022 - NPZ format reuploaded to fix event polarity corruption that was reported on GitHub
  • 04/14/2022 - EVIMO2v2 released

Motion Segmentation / Object Recognition

A tabletop scenario (shot with all 4 cameras up-close) with objects moving independently from the camera. Pixelwise masks, depth maps and trajectories are provided. This dataset is also suitable for object recognition tasks.

Camera Downloads Sample Sequence
flea3_7 .npz (33 GB)
.txt (22 GB)
left_camera .npz (1.8 GB)
.txt (2.7 GB)
right_camera .npz (1.7 GB)
.txt (2.5 GB)
samsung_mono .npz (2.4 GB)
.txt (3.1 GB)

ROS Bags (raw data)

eval sequences
Sequence Video
scene13_dyn_test_00_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene13_dyn_test_05_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene14_dyn_test_03_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene14_dyn_test_04_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene14_dyn_test_05_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene15_dyn_test_01_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene15_dyn_test_02_000000
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left events+seg left depth right events+seg right depth
scene15_dyn_test_05_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
train sequences
Sequence Video
scene10_dyn_train_00_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene10_dyn_train_01_000000
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left events+seg left depth right events+seg right depth
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left events+seg left depth right events+seg right depth
scene10_dyn_train_04_000000
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left events+seg left depth right events+seg right depth
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left events+seg left depth right events+seg right depth
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left events+seg left depth right events+seg right depth
scene14_dyn_test_01_000000
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left events+seg left depth right events+seg right depth
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left events+seg left depth right events+seg right depth
scene15_dyn_test_00_000000
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left events+seg left depth right events+seg right depth
scene15_dyn_test_03_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene15_dyn_test_04_000000
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left events+seg left depth right events+seg right depth
scene15_dyn_test_06_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene6_dyn_train_03_000000
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left events+seg left depth right events+seg right depth
scene9_dyn_train_01_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene9_dyn_train_02_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene9_dyn_train_06_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth

Motion Segmentation in Low Light

These sequences were shot in low light - they feature high amounts of noise and are meant to be extremely challenging.

Camera Downloads Sample Sequence
flea3_7

Not Available

left_camera .npz (0.2 GB)
.txt (0.2 GB)
right_camera .npz (0.2 GB)
.txt (0.3 GB)
samsung_mono .npz (0.2 GB)
.txt (0.2 GB)

ROS Bags (raw data)

eval sequences
Sequence Video
scene16_d_dyn_test_01_000001
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene16_d_dyn_test_04_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
train sequences
Sequence Video
scene16_d_dyn_test_00_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene16_d_dyn_test_02_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
scene16_d_dyn_test_03_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth

Structure from Motion / Object Recognition

The sequences feature a variety of objects scattered on the tabletop, but the scene is rigid (no independent motion). The objects provide depth variation and some degree of diversity from recording to recording, and additionally allow to evaluate object recognition algorithms (pixelwise masks are provided).

Camera Downloads Sample Sequence
flea3_7 .npz (169 GB)
.txt (113 GB)
left_camera .npz (22 GB)
.txt (34 GB)
right_camera .npz (23 GB)
.txt (35 GB)
samsung_mono .npz (10 GB)
.txt (14 GB)

ROS Bags (raw data)

eval sequences
Sequence Video
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train sequences
Sequence Video
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flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
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left events+seg left depth right events+seg right depth

Structure from Motion in Low Light

These sequences were shot in low light - they feature high amounts of noise and are meant to be extremely challenging.

Camera Downloads Sample Sequence
flea3_7 .npz (0.6 GB)
.txt (0.7 GB)
left_camera .npz (1.4 GB)
.txt (1.9 GB)
right_camera .npz (1.5 GB)
.txt (2.0 GB)
samsung_mono .npz (1.4 GB)
.txt (1.7 GB)

ROS Bags (raw data)

eval sequences
Sequence Video
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left events+seg left depth right events+seg right depth
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flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
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train sequences
Sequence Video
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left events+seg left depth right events+seg right depth
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Rudimentary Motion in Planar Scenes

These sequences use primitive scenarios with rudimentary motions and are provided primarily for sanity testing, benchmarking and debugging of software.

Camera Downloads Sample Sequence
flea3_7 .npz (65 GB)
.txt (43 GB)
left_camera .npz (7.0 GB)
.txt (11 GB)
right_camera .npz (7.5 GB)
.txt (11 GB)
samsung_mono .npz (6.1 GB)
.txt (8.2 GB)

ROS Bags (raw data)

eval sequences
Sequence Video
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left events+seg left depth right events+seg right depth
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flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth

Rudimentary Motion in Planar Scenes in Low Light

These sequences were shot in low light - they feature high amounts of noise and are meant to be extremely challenging.

Camera Downloads Sample Sequence
flea3_7 .npz (1.7 GB)
.txt (2.1 GB)
left_camera .npz (5.7 GB)
.txt (8.5 GB)
right_camera .npz (0.6 GB)
.txt (0.9 GB)
samsung_mono .npz (2.7 GB)
.txt (3.6 GB)

ROS Bags (raw data)

eval sequences
Sequence Video
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left events+seg left depth right events+seg right depth
checkerboard_d_flat_lr_000000
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left events+seg left depth right events+seg right depth
checkerboard_d_flat_rot_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
checkerboard_d_flat_rot_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
checkerboard_d_flat_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
checkerboard_d_tilt_fb_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
checkerboard_d_tilt_rot_z_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_0_d_fb_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_0_d_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_0_d_rot_z_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_flat_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_flat_rot_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_flat_rot_z_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
checkerboard_d_flat_rot_z_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
checkerboard_d_tilt_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
checkerboard_d_tilt_rot_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
checkerboard_d_tilt_rot_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
checkerboard_d_tilt_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_0_d_rot_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_0_d_rot_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_0_d_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_1_d_fb_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_1_d_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_1_d_rot_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_1_d_rot_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_1_d_rot_z_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
depth_var_1_d_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_flat_rot_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_flat_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_tilt_fb_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_tilt_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_tilt_rot_lr_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_tilt_rot_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_tilt_rot_z_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth
tabletop_d_tilt_ud_000000
flea3_7 rgb+seg flea3_7 depth sam events+seg sam depth
left events+seg left depth right events+seg right depth

Videos

Complete archive of the videos for each camera. The videos contain the data for the camera with a segmentation overlay and the depth.

These videos can be previewed using the "Click to show videos" buttons in each section above.

Camera Download Links
flea3_7 .mp4 (2.3GB)
left_camera .mp4 (4.7GB)
right_camera .mp4 (4.0GB)
samsung_mono .mp4 (4.7GB)

Summary Statistics

Sequence Type # Train Sequences # Test Sequences Minutes of Train Minutes of Test GB of DVS
(NPZ download)
GB of RGB
(NPZ download)
Motion Segmentation 21 8 2.74 0.51 6.0 33.0
Motion Segmentation
(Low Light)
3 2 0.36 0.14 0.6 N/A
Structure from Motion/Object Recognition 52 10 16.17 2.45 54.9 169.0
Structure from Motion/Object Recognition (Low Light) 5 6 2.56 1.37 4.3 0.6
Rudimentary Motion in Planar Scenes N/A 31 N/A 6.96 21.0 64.8
Rudimentary Motion in Planar Scenes (Low Light) N/A 35 N/A 7.89 9.0 1.7
Totals 81 92 21.83 19.32 95.8 269.1

Full Camera Availability and Data Duration Matrix

Download spreadsheet


License

This dataset is provided under the Creative Commons Attribution-ShareAlike 4.0 International public license (CC BY-SA 4.0). This means that if the data is redistributed, attribution must be given and the license cannot be changed. Commercial use and adaptation are allowed. A summary of the terms is available here.